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1、+2TABLE OF CONTENTS+INTRODUCTION AND AUDIENCE OVERVIEW|3KEY INSIGHTS|4THE CURRENT STATE OF THE DATA MANAGEMENT SOLUTIONS LANDSCAPE|5THE PAST OF DATA MANAGEMENT|18 THE FUTURE OF DATA MANAGEMENT|26CLOSING WORDS BY AIVEN|36APPENDIX|383+INTRODUCTION AND AUDIENCE OVERVIEWIn recent years,companies that ha

2、ve embraced digital native practices have experienced considerable change and growth by placing technology at the heart of their businesses.These companies follow a culture that promotes innovation,uses agile operating models,and often relies on predictive analytics to maximise their performance to

3、deliver high quality results.In turn,this comes with a lot of data to manage and a unique set of challenges that manifest in their data infrastructure projects.In this report,commissioned by Aiven and authored by SlashData,we investigate the evolution of the data management landscape at digital nati

4、ve companies1in response to changing environments(both internal and external).With the ongoing effects of the recent global pandemic and the European energy crisis,many businesses lost access to physical workplaces or had to shut down entirely.On the positive side,adapting to change and overcoming e

5、xternal challenges builds resilience and stamina that can even lead to growth.For companies that aim to scale fast,rapid change and quick response are part of the challenge.We will primarily focus on the big picture of tech and tooling decisions,and how practices differ based on company growth rates

6、.We asked our respondents to identify the number of employees that their company has and by how much this number has changed over the past 12 months.For organisations that have more than 25 employees,we define those that have increased their full-time equivalent headcount by more than 50%as fast-gro

7、wing,and others as having experienced conservative growth.It is important to identify the practices and trends that can be of benefit to either business model.In this report,we use the term fast growth to refer to the overall approach of swift innovation and response to change that is necessary for

8、companies that are focussedon increasing their personnel and tooling.We will begin by examining the current state of adoption of the most popular data management systems and their associated hosting preferences among our respondents.Following this,we will look at the past and the future of data mana

9、gement by taking a look at which data management tools our respondents stopped using and which ones they are planning to adopt.To supplement this,we will take a deep dive into the reasons why they have adopted the data management tools that they are currently using and what led them to find alternat

10、ive solutions than those that they have previously tried or evaluated.Finally,we will shift our focus towards the perception of the future importance levels of certain selection criteria among technology professionals when considering a Database as a Service(DBaaS)vendor.The findings of this report

11、are based on data collected from an online survey designed,produced,and carried out by SlashData,which reached nearly 500 IT professionals involved in data infrastructure operations at digital native companies worldwide over a period of four weeks in Q3 20222.Profile distributions of the respondents

12、 can be found in the appendix.1We define digital native companies as those founded on,or that rely heavily upon,digital native practices.Digital native practices include,among others,use of cloud technologies(e.g.DBaaS),agile/lean methodologies,and involvement in DevOps activities(e.g.CI/CD).2Job ti

13、tles/roles of these respondents:database administrator,IT manager,IT/system administrator,DevOps engineer/specialist,tech/engineering team lead,CIO/CTO/CSO,IT security manager,network security engineer,site reliability engineer.4+KEY INSIGHTS Companies with an eye for scaling up are,on average,16%mo

14、re likely to use fully-managed services and are highly focused on search technologiesand event streaming/message queue systems.Faster-growing companies tend to be more likely to adopt open source search technologies,with OpenSearch emerging as the most popular search technology among them.43%of thos

15、e who work for companies with fast-growth business models prioritise service availability and disaster recovery capabilities when adopting data management products.While data model suitability is at the forefront of reasons for adopting data management tools,pricing is often the primary factor when

16、it comes to finding alternative solutions.56%of respondents are looking to adopt at least one new data management system type in the near future,with those who work for fast-growing companies being 20%more likely to do so than those who work for companies with conservative growth rates.As businesses

17、 seek to take advantage of the continuous digitisation of the modern world,event streaming and message queues are on track to become the second most popular data management systems type among digital native companies in the near future.Digital native companies,particularly those that are fast-growin

18、g,are ready to embrace open source data management technologies when selecting DBaaS vendors.Digital native companies are becoming more willing to prioritise reducing their environmental footprint over optimising costs when selecting a DBaaS vendor to ensure that their actions help protect the envir

19、onment.THE CURRENT STATE OF THE DATA MANAGEMENT SOLUTIONS LANDSCAPE+62023 state of data management solutions for digital natives1.The current state of the data management solutions landscape+A.Overview of the data management solutions landscapeallow businesses to adapt to the ever-changing landscape

20、 of information storage needs and other shifts throughout the industry.The vast majority of data infrastructure operations professionals at digital native companies use a large variety of data management system types simultaneously six on average to optimise their business operations.While relationa

21、l databases take a clear lead in adoption,we find that non-relational databases such as search technologies and event streams are not far behind.Further analysis reveals that there is a roughly even split between the usage of fully-managed(40%)and self-managed(43%)solutions at digital native compani

22、es3.We find that users of graph databases are the most likely to favour self-managed solutions,with 46%of them choosing to exclusively self-manage and a further 18%using both management types.On the other end of the spectrum,users of search technologies show a strong preference towards adopting full

23、y-managed services.Commercial offerings from tech giants such as Google and Microsoft take the lead across most database types.For instance,Googles products are used by more than half of those who use event streaming and message queue systems.Similarly,Microsoft SQL Server and Microsoft Access are t

24、he two most popular relational databases.With increased dependence on data,digital native companies rely heavily on different types of data management systems to ensure that their business processes run smoothly and are adaptive to change.However,the solutions that they choose are highly dependent o

25、n what they need to do with their data.In addition to this,some may choose to self-manage while others find advantages in using fully-managed services.Relational databases are the most popular type of data management systems,with the vast majority of respondents(78%)having used them in the past year

26、,either in a self-managed setting or through a fully-managed service.This comes as no surprise,since most digital native businesses work with interlinked sets of data in one way or another.Despite being a staple of data storage since their introduction,the explosive growth of data volume posed chall

27、enges for relational databases.Non-relational databases,such as search technologies and document stores,rose to the occasion.They are able to store data in non-tabular form and3In comparison,IT professionals from non-digital native companies show a much stronger preference towards self-managed solut

28、ions(47%)over fully-managed services(41%).72023 state of data management solutions for digital natives1.The current state of the data management solutions landscape+67%57%61%61%63%69%71%72%73%78%40%39%41%40%36%38%39%47%48%35%17%15%16%13%18%20%17%13%19%22%43%46%43%47%46%43%44%40%32%43%Average across

29、database typesWide-column storesColumnar/data warehousesTime seriesGraphDocument storesKey-value storesEvent streaming/message queuesSearch technologiesRelationalFully-managed onlyBothSelf-managed onlyIT professionals who use search technologies are the most likely to opt for fully-managed servicesU

30、sage of data management systems%of respondents(n=497)Types of hosting by data management systems%of respondents using each data management system(n=497)82023 state of data management solutions for digital natives1.The current state of the data management solutions landscape+Commercial offerings are

31、the most popular across many data management system types%of respondents who are currently using each data management system type(n=497)52%46%41%36%35%Microsoft SQL ServerMicrosoft AccessMySQLOraclePostgreSQLRelational48%45%37%27%19%Microsoft Azure SearchAmazon CloudSearchOpenSearchElasticsearchVirt

32、uosoSearch technologies40%39%29%25%23%RedisOracle Berkeley DBMemcachedetcdRocksDBKey-value stores38%35%31%30%30%GraphiteTimescaleDBPrometheusInfluxDBQuestDBTime series53%52%33%26%25%Google BigQueryAmazon RedshiftDatabricksSnowflakeApache PinotColumnar/data warehouses44%44%41%35%34%Google Cloud Fires

33、toreMicrosoft Azure Cosmos DBAmazon DynamoDBOracle NoSQLMongoDBDocument stores54%50%35%35%33%Google Cloud DataflowGoogle Cloud PubSubAmazon KinesisIBM Event StreamsIBM MQEvent streaming/message queues50%37%28%28%21%Microsoft Azure Cosmos DBAmazon NeptuneGraphDBOrientDBNeo4jGraph57%54%51%45%28%Micros

34、oft Azure Table StorageMicrosoft Azure Cosmos DBGoogle Cloud BigtableAmazon KeyspacesDatasatax EnterpriseWide-column storesMost popular data management tools by category92023 state of data management solutions for digital natives1.The current state of the data management solutions landscape+B.How co

35、mpany growth affects data management solution choicesOutside of the top three,the overall interest in different types of data management systems falls sharply among the respondents working for fast-growing companies.For instance,only 61%of data management professionals from fast-growing companies us

36、e document stores,despite being the fifth most popular technology.In contrast,document stores are used by 80%of their conservative-growth counterparts,among whom it is the most popular data management system type.Looking at technology choices in terms of company growth reveals clear differences betw

37、een fast-growing companies and their counterparts.We find that fast-growing companies tend to focus on search technologies and event streaming/message queue systems.However,relational databases are still used by 71%of data infrastructure operations professionals from fast-growing companies,and are t

38、he most likely to increase in popularity in the future,as we will see later in this report.102023 state of data management solutions for digital natives1.The current state of the data management solutions landscape+76%75%80%79%80%72%69%66%74%79%77%71%64%61%59%58%57%55%Search technologiesEvent stream

39、ing/message queuesRelationalKey-value storesDocument storesGraphTime seriesWide-column storesColumnar/data warehousesUsage of data management systems by company growth rateConservative growthFast growthFast-growing companies are highly focused on search technologies and event streaming/message queue

40、 systems%of respondents who work for companies of each growth rate(n=389)112023 state of data management solutions for digital natives1.The current state of the data management solutions landscape+We find that 71%of those who work for fast-growing businesses use fully-managed services for search tec

41、hnologies in some capacity,while only 29%choose to exclusively self manage.While event streaming and message queues closely follow this pattern,fast-growing companies show no significant management preferences when it comes to relational databases.This suggests that using fully-managed services for

42、search technologies and event streaming/message queues can be highly advantageous,while using them for relational databases has the lowest impact on company growth.With the exception of search technologies,companies with conservative growth rates show a strong preference towards self-managed solutio

43、ns.Conversely,those who work for fast-growing companies tend to lean towards fully-managed services.In fact,fast-growing companies are,on average,16%more likely to use a fully-managed service than their counterparts with conservative growth rates.Spending less time on managing their database instanc

44、es themselves allows fast-growing companies to focus their efforts on other parts of their businesses that help them scale faster.122023 state of data management solutions for digital natives1.The current state of the data management solutions landscape+44%57%55%34%37%37%18%12%16%19%17%26%38%32%29%4

45、6%47%37%Average across other data managementsystemsEvent streaming/message queuesSearch technologiesAverage across other data managementsystemsEvent streaming/message queuesSearch technologiesTypes of hosting by company growth rateFully-managed onlyBothSelf-managed onlyIT professionals in fast-growi

46、ng companies are more likely to rely on DBaaS solutions%of respondents using each data management system type who work for companies of each growth rate(n=389)ConservativegrowthFastgrowth132023 state of data management solutions for digital natives1.The current state of the data management solutions

47、 landscape+The popularity rankings of the top event streaming and message queue systems have no significant differences based on company growth rate.Furthermore,we see a very strong preference for commercial offerings in this category,suggesting that their open source alternatives may be too difficu

48、lt to set up and maintain.In practice,using open source solutions such as Apache Kafka requires a lot of expertise and can take a long time to fully implement.Conversely,opting for commercial systems allows digital native companies to deploy their projects very quickly,receive technical support,and

49、get access to streamlined APIs and SDKs.When it comes to relational database solutions,those who work for companies with conservative growth rates show a clear preference towards Microsofts products.In fact,over half of them use Microsoft Access and Microsoft SQL Server,which are substantially ahead

50、 of the next most popular product,Oracle.On the other hand,Google Spanner takes the number one spot among their fast-growing counterparts with an adoption rate of 49%.Similar to the case of data management systems,we observe some major differences in the usage rates of specific tools across companie

51、s of different growth rates.With adoption rates that are double that of their next closest competitors,Microsoft Azure Search and Amazon CloudSearch dominate the search technologies rankings for companies with conservative growth rates.However,these two commercial tools see high levels of competitio

52、n from their open source alternatives among respondents working for fast-growing companies.OpenSearch emerges as the most popular search technology for fast-growing companies and Elasticsearch sees a similar level of success.This suggests that fast-growing companies are more likely than average to a

53、dopt open source technologies when it comes to search technologies.142023 state of data management solutions for digital natives1.The current state of the data management solutions landscape+47%45%43%39%21%26%50%51%17%15%OpenSearchAmazon CloudSearchMicrosoft Azure SearchElasticsearchSplunkSearch tec

54、hnologiesFast-growing companies are more likely to adopt open source search technologies%of respondents who are using each data management system type(n=379)58%52%36%35%32%50%49%33%36%33%Google Cloud DataflowGoogle Cloud PubSubAmazon KinesisIBM Event StreamsIBM MQEvent streaming/message queuesFast g

55、rowthConservative growth49%48%43%39%37%29%54%40%57%37%Google SpannerMicrosoft SQL ServerOracleMicrosoft AccessAmazon AuroraRelationalMost popular data management tools by category and company growth rate152023 state of data management solutions for digital natives1.The current state of the data mana

56、gement solutions landscape+C.Top features IT professionals look for when selecting data management toolsAs companies grow,they take on more projects and explore new avenues in their operations.With this,the importance given to some adoption criteria becomes amplified for businesses that experience h

57、igh growth rates.Features such as data model suitability and integration capabilities with other systems carry an increased level of importance for those who use fully-managed services.Since those who work for fast-growing companies are significantly more likely to opt for fully-managed solutions,th

58、ey value these features far more than those who work for companies with conservative growth rates.For instance,45%of respondents working at fast-growing companies say that integration capabilities with other systems carries a high level of importance for them,while only 29%of their conservative-grow

59、th counterparts do the same.While different businesses may use similar types of data,the way they use it depends on the nature of their projects.In turn,this dictates which data management tools they end up choosing to complement their operations.In this section,we will explore the top criteria on w

60、hich data operations professionals base their choice in data management tools.162023 state of data management solutions for digital natives1.The current state of the data management solutions landscape+Data model suitability is at the forefront of adoption criteria for data management tools%of respo

61、ndents who are currently using any data management tool(n=489)3%6%10%12%14%16%16%16%20%21%21%22%23%24%28%29%31%33%36%My boss said so/not my decisionIts company policyCommunityLearning curveLicensingDocumentation&sample codeBuilt on open source technologiesRead/write performanceQuery performanceScala

62、bilityPricingEase&speed of developmentEase of installation&deploymentTechnical supportFamiliarity with the database or query languageSecurity&complianceAvailability/disaster recovery capabilitiesIntegration with other systemsData model suitabilityTop reasons for adopting a data management tool172023

63、 state of data management solutions for digital natives1.The current state of the data management solutions landscape+Technical support is 70%more important for fast-growing companies%of respondents who are currently using any data management solution by company type(n=381)26%21%35%18%25%27%29%33%11

64、%12%23%31%36%43%45%46%ScalabilityQuery performanceSecurity&complianceTechnical supportFamiliarity with thedatabase or querylanguageAvailability/disasterrecovery capabilitiesIntegration with othersystemsData model suitabilityBiggest differences in adoption criteria for data management tools by compan

65、y growth rateConservative growthFast growthTHE PAST OF DATA MANAGEMENT+2023 state of data management solutions for digital natives192.The past of data management+A.Looking for the alternativesTaking a look at individual data management system types reveals that the replacement rates of data manageme

66、nt tools show a significantly lower set of variations than their corresponding adoption rates.This suggests that most replacement cases are likely due to the benefits of other products,rather than critical failures of the replaced ones.For example,while IBM Event Streams and Apache Kafka show simila

67、r results when it comes to the overall replacement rates,the former is significantly more popular.Before adopting a new solution,data management professionals must consider all viable alternatives to help them make the best choice for their businesses.As businesses evolve,they may also find that the

68、ir existing systems have become inadequate for their current operations.In turn,these factors lead customers to find alternative databases.2023 state of data management solutions for digital natives202.The past of data management+Most replacement cases are likely due to the benefits of other product

69、s,rather than critical failures%of respondents who are using or are planning to use each data management system type(n=497)13%12%11%11%11%MySQLIBM Db2TeradataFilemakerSAP HANARelational10%10%7%7%6%SolrMeilisearchAlgoliaCoveoArangoDBSearch technologies11%9%8%8%7%ksqlDBIBM Event StreamsApache KafkaIBM

70、 MQHeronEvent streaming/message queues13%13%12%12%11%HazelcastRedisRocksDBOracle Berkeley DBRiak KVKey-value stores17%13%11%11%11%OrientDBMarkLogicArangoDBCouchDBRealmDocument stores16%12%11%11%10%AllegroGraphArangoDBJanusGraphVirtuosoMemgraphGraph18%15%14%13%12%FaunaInfluxDBRRDtoolOpenTSDBPrometheu

71、sTime series16%15%14%14%12%ClickHouseApache DruidMonetDBApache PinotVerticaColumnar/data warehouses17%13%11%9%9%AccumuloCassandraScyllaDBGoogle Cloud BigtableMicrosoft Azure Cosmos DBWide-column storesMost frequently replaced data management tools by category2023 state of data management solutions f

72、or digital natives212.The past of data management+While the replacement rates of relational databases and search technologies are a lot more balanced between the two groups of respondents,we still see some big differences.For example,fast-growing companies are likely to replace legacy commercial dat

73、abases such as Teradata.On the other hand,as OpenSearch and Elasticsearch are significantly more popular among those who work for fast-growing companies,their below-average replacement rates suggest that they are highly suitable for the search technologies needs of fast-growing companies.Earlier,we

74、saw that the top event streaming and message queue systems had the least significant differences in adoption based on company growth rates.However,this is not the case when it comes to replacement rates.Those who work for companies with conservative growth rates are,on average,40%more likely to repl

75、ace a product in this category than their fast-growing counterparts.2023 state of data management solutions for digital natives222.The past of data management+11%9%8%6%6%11%10%7%9%7%MeilisearchSolrAlgoliaElasticsearchCoveoSearch technologiesFast-growing companies are less likely to replace event str

76、eaming and message queue services%of respondents who are using or are planning to use each data management system type(n=388)10%9%8%7%7%14%12%8%11%9%ksqlDBApache KafkaIBM Event StreamsIBM MQKapacitorEvent streaming/message queuesFast growthConservative growth11%11%11%10%10%10%11%7%13%9%IBM Db2Filema

77、kerTeradataMySQLSAP HANARelationalMost frequently replaced data management tools by category and growth rate2023 state of data management solutions for digital natives232.The past of data management+B.Top reasons why IT professionals replace data management toolsAs businesses grow,expanding operatio

78、ns too quickly can put more strain on data infrastructure.This can lead to slow response times or even downtime if not properly addressed.Companies often rely on quality of service management APIs to monitor their systems workloads and ensure high performance.In turn,any issues with these APIs can b

79、e detrimental to business operations,making it the most frequently reported reason for replacing a data management product among those who work for fast-growing companies.Moving fast and exploring new ideas comes with an increased risk of something going wrong.To combat this,43%of those who work for

80、 fast-growing companies prioritise service availability and disaster recovery capabilities when it comes to adopting a data management tool.In addition,19%of them have previously replaced a data management tool based on inadequate backup/snapshot functionality.However,only 9%of their conservative-gr

81、owth counterparts have mentioned this feature as one of the main reasons for replacing a data management tool in the past,as they are less likely to try new things.Data model suitability may be key when looking for a new data management product,but when it comes to replacing one,pricing plays the mo

82、st important role.28%of respondents reported pricing as one of the main reasons for replacing such products while only 21%did so due to suitability issues.While a given product may be highly suitable and have good integrations with other systems,it may not be a feasible choice for those with limited

83、 budgets.This is most prominent among those who work for small businesses with up to 200 employees,34%of whom mention pricing as one of their top reasons for replacing a data management solution.On the other hand,large enterprises care most about receiving high quality technical support.2023 state o

84、f data management solutions for digital natives242.The past of data management+Pricing is the leading cause for replacing of data management tools%of respondents who have replaced a data management tool in the last 12 months(n=326)10%11%12%13%15%15%16%17%17%20%21%22%23%26%27%27%28%My boss said so/no

85、t my decisionDocumentation&sample codeCommunityBackup/snapshot functionalityUsability of admin consoleFamiliarity with the database or query languageIts company policyLearning curveRead/write performanceEase&speed of developmentData model suitabilityQuery performanceScalabilityTechnical supportQuali

86、ty of service management APIIntegration with other systemsPricingTop reasons for replacing a data management tool2023 state of data management solutions for digital natives252.The past of data management+37%of those who work for fast-growing businesses have replaced a data management tool based on q

87、uality of service management APIs%of respondents who have replaced a data management tool in the last 12 months by company type(n=251)21%9%9%12%16%12%37%29%13%17%19%19%22%23%23%37%Read/writeperformanceCommunityBackup/snapshotfunctionalityFamiliarity with thedatabase or querylanguageEase&speed ofdeve

88、lopmentUsability of adminconsoleIntegration with othersystemsQuality of servicemanagement APIBiggest differences in replacement criteria for data management tools by company growth rateConservative growthFast growthTHE FUTURE OF DATA MANAGEMENT+2023 state of data management solutions for digital nat

89、ives273.The future of data management+A.Planned use of data management systems and toolsRelational databases have a clear lead in adoption over the other data management systems,and this is unlikely to change in the near future.However,with the continuous digitisation of our everyday lives and incre

90、ased reliance on artificial intelligence,the demand for streaming data has never been higher.In turn,businesses are looking to implement procedures that can take advantage of this evolution.This is also reflected in our data,as event streaming and message queues are on track to become the second mos

91、t popular data management system type among digital native companies.With the constant evolution of data in our digital world,businesses take up new ventures and look to adopt new technologies as they grow.The same applies to data management systems.56%of respondents are looking to adopt at least on

92、e new data management system type in the near future.A deeper dive reveals that those who work for fast-growing companies are 20%more likely to do so than those who work for companies with conservative growth rates.2023 state of data management solutions for digital natives283.The future of data man

93、agement+7%8%10%10%10%11%11%11%13%Wide-column storesKey-value storesDocument storesTime seriesColumnar/data warehousesRelationalGraphSearch technologiesEvent streaming/message queuesPlanning to use data management systemsEvent streaming and message queue systems are the most likely data management sy

94、stem type to increase in popularity%of respondents(n=497)2023 state of data management solutions for digital natives293.The future of data management+Despite this,search technologies are likely to retain their top spot in usage at fast-growing companies.36%of these respondents have indicated that th

95、ey are planning to adopt Meilisearch in the near future.Due to its currently low adoption rate(15%)among these respondents,however,it is unlikely that Meilisearch will overtake the current leaders.In contrast,31%of individuals from fast-growing companies have indicated that they are planning to use

96、Elasticsearch.This suggests that Elasticsearch has high potential to advance among those who work for fast-growing companies.Interestingly,relational databases are set to gain the highest number of new users at fast-growing companies.While there is no significant variance in future adoption plans be

97、tween relational,or any other type of,data management tools4,we observe some major differences when taking company growth rates into account.For instance,many fast-growing companies are looking to switch to open source alternatives such as Hive and PostgreSQL in the near future but are also interest

98、ed in Oracle.On the other hand,26%of respondents who work for companies with conservative growth rates have indicated that they are planning to use Google Spanner.4See the appendixfor the top-five rankings of individual data management tools in terms of future adoption plans.2023 state of data manag

99、ement solutions for digital natives303.The future of data management+8%7%11%11%7%8%10%6%10%6%7%8%9%11%12%14%14%17%Key-value storesWide-column storesColumnar/data warehousesGraphDocument storesTime seriesEvent streaming/message queuesSearch technologiesRelationalPlanning to use data management system

100、s by company growth rateFast growthConservative growthIT professionals at fast-growing companies are most likely to start using relational databases%of respondents(n=389)2023 state of data management solutions for digital natives313.The future of data management+36%31%31%30%29%23%25%23%20%24%Meilise

101、archElasticsearchCoveoCreateDBAmazon CloudSearchSearch technologiesElasticsearch has a high potential to take the lead among fast-growing companies%of respondents who are using or are planning to use each data management system type(n=388)32%32%30%29%28%23%25%26%21%25%Azure EventHubAmazon KinesisCel

102、eryActiveMQRabbitMQEvent streaming/message queuesFast growthConservative growth32%30%27%27%24%22%16%21%20%25%HiveOracleFilemakerPostgreSQLSQLiteRelationalPlanning to use management tools by category and growth rate2023 state of data management solutions for digital natives323.The future of data mana

103、gement+B.Future outlook on fully-managed servicesWhile all of the listed features received a positive NIS,security and performance separate themselves from the rest as the most likely features to grow in importance.Taking performance as an example,we observe that 77%of respondents think that it will

104、 play a bigger role in selecting a DBaaS vendor in the future,while only 1%have an opposing view.This results in a NIS of+76,indicating a strong likelihood that this feature will increase in importance in the future.The proportion of respondents who expect pricing and cost optimisation to become mor

105、e important in the future is similar to that of server locations,documentation,and being cloud-agnostic.However,the proportion of respondents who expect the importance of this aspect to decrease is significantly higher than that of any other aspect.This results in the lowest NIS in our survey,sugges

106、ting that pricing and cost optimisation is the least likely aspect to grow in importance when selecting a DBaaS vendor.This is likely because it is a category that is well understood by DBaaS vendors,leaving little room for innovation and improvement on pricing and cost optimisation.In this section,

107、we will explore the future outlook on a selection of product features that technology professionals consider when selecting a DBaaS vendor.We asked respondents whether the importance of certain DBaaS features will grow,stay the same,or decrease in the future.To determine this,we will calculate a net

108、 increase score(NIS)by subtracting the percentage of those who expect a decrease in importance from the percentage of those who expect an increase.This does not represent the amount by which the importance levels of each one of these features will change in the future.Instead,the NIS broadly represe

109、nts the implied likelihood of a change happening in a particular direction.2023 state of data management solutions for digital natives333.The future of data management+Security and performance are the most likely aspects to grow in importance when selecting a DBaaS vendor%of respondents and net incr

110、ease scores(n=424)77%77%70%66%64%59%57%53%52%52%53%21%22%28%31%35%38%41%44%44%43%35%3%3%4%4%13%SecurityPerformanceScalabilityOffering solutions based on open source technologiesSustainability/being environmentally friendlyAccess controlTechnical supportLocation of serversDocumentationBeing cloud-agn

111、osticPricing/cost optimisationFuture sentiment breakdownWill growWill stay the sameWill decrease+76+76+68+64+62+55+55+50+48+48+40Net Increase Score2023 state of data management solutions for digital natives343.The future of data management+In recent years,there has been a growing interest in sustain

112、ability by both businesses and consumers around the world.By choosing a DBaaS vendor that is committed to sustainable practices,digital native companies can ensure that their actions help protect the environment.Our data suggest that there is a high likelihood of this becoming more important when se

113、lecting a DBaaS vendor(+62).In fact,this is significantly higher than that of pricing and cost optimisation(+40),suggesting that digital native companies are becoming more willing to prioritise reducing their environmental footprint over optimising costs.Interestingly,we find that factors such as co

114、mpany size,growth rate,and location have little impact on the highly positive outlook of sustainability.Earlier in this report,we saw that fast-growth companies are more likely to adopt open source data management products than their conservative-growth counterparts.Conversely,the latter were shown

115、to be more concerned with scalability of such products.Here,we see this set of priorities extends to the future values of these groups.Our data suggest that fast-growing companies are very likely to place a higher value on open source technologies when selecting a DBaaS vendor in the future.Converse

116、ly,there is a similar likelihood of scalability becoming more important in the future for their conservative-growth counterparts.2023 state of data management solutions for digital natives353.The future of data management+Fast-growing companies are ready to embrace open source data management techno

117、logies when selecting DBaaS vendorsNet increase scores(n=389)+39+49+44+44+55+72+62+52+59+79+75+48+52+52+53+54+59+61+62+70+70+75Pricing/cost optimisationLocation of serversBeing cloud-agnosticDocumentationTechnical supportScalabilitySustainability/being environmentally friendlyAccess controlOffering

118、solutions based on open source technologiesSecurityPerformanceNet Increase Score by company growth rateFast growthConservative growthCLOSING WORDS BY AIVEN+2023 state of data management solutions for digital natives374.Closing words by Aiven+On the other hand,the research confirms what we do see in

119、our customers.Digital native companies cannot rely on a limited number of data management technologies.Instead,they are building data pipelines with a multitude of technologies that cover all key data use cases streaming,storage,and analytics.The fact that the majority of companies were looking to a

120、dd new data technologies in the near future shows how this trend will continue.Finally,we were happy to confirm our experience that the usage of managed services by digital native companies in the data management space is increasing.The fact that nimble and high-growth digital native companies use t

121、hem more than others tells us a lot about the value managed services bring.When you are growing fast,you dont want to be bothered with low-value tasks but want to focus on things that really move the needle.Aiven is a provider of fully-managed,open source data management solutions.When we commission

122、ed the creation of this“2023 state of data management solutions for digital natives”report by SlashData,we came in with our own thoughts and assumptions on what the results would show,based on insights from discussions with our customers.Many of those assumptions were proven but there were also surp

123、rises along the way.One of the surprises was how heavily respondents still relied on commercial data management tools over their open source alternatives.This is obviously not all black and white,as many commercial offerings are based on open source technologies,but we did expect to see technologies

124、 such as PostgreSQL and Apache Kafka more widely used.On the positive side,the importance of open source based offerings is increasing,especially among digital native companies that follow a fast-growth business strategy.The key take-away for us is that more than ever,we need to continue educating t

125、he market on the benefits of open source.APPENDIX+39Appendix+37%23%10%10%8%5%4%3%1%North AmericaWestern Europe&IsraelEast Asia ex.GreaterChinaMiddle East&AfricaGreater China areaSouth AsiaEastern EuropeRussia&Former CISSouth AmericaOceaniaRegional distribution of respondents%of respondents(n=497)40A

126、ppendix+30%28%25%22%19%14%13%8%8%Database administratorIT managerIT/system administratorDevOps engineer/specialistTech/engineering team leadCIO/CTO/CSOIT security managerNetwork security engineerSite reliability engineer(SRE)Job titles/roles of respondents%of respondents(n=497)41Appendix+14%8%39%39%

127、Growth rate%of respondents(n=497)25 employeesI dont knowConservative growthFast growth14%13%13%24%14%13%9%2-2526-7576-200201-500501-10001000-5000 5000Number of employeesSize of the organisation%of respondents(n=497)Large enterprisesMid-sized businessesSmall businesses42Appendix+43%22%20%18%15%12%12%

128、12%12%11%11%10%10%8%6%6%6%6%5%5%4%4%4%1%Software products and services(SaaS)Data analytics/Business intelligence(BI)products and servicesEducation,training,and academic/scientific researchTelecommunications and networksRetailHardware productsHealth,medical,biotechnology,and pharmaceuticalsBusiness c

129、onsulting,legal services,HR&recruitment servicesFinancial services&bankingManufacturingMarketing and advertising servicesEntertainment,media and newsTransportation and logisticsConstructionEnergy(incl.oil,gas,electricity,and water)Food and agricultureGovernment and defenceReal estateInsuranceTourism

130、/hospitalityAutomotive and boatingHumanitarian aid and other non-profit organisationsAerospace and aviationOtherActive industry of the organisation%of respondents(n=494)43Appendix+24%23%22%22%21%HiveSAP HANAAmazon AuroraSQLitePostgreSQLRelational27%26%25%25%23%MeilisearchElasticsearchAmazon CloudSea

131、rchCoveoMarkLogicSearch technologies27%26%25%25%25%Amazon KinesisCeleryAzure EventHubRabbitMQApache FlinkEvent streaming/message queues26%26%24%24%23%InfinispanAerospikeHazelcastRedisRiak KVKey-value stores27%25%25%24%24%CouchbaseMarkLogicMongoDBRealmFirebase Realtime DatabaseDocument stores29%28%27

132、%27%27%FaunaGraphDBVirtuosoJanusGraphNeo4jGraph31%28%28%28%27%kdb+VictoriaMetricsPrometheusRRDtoolM3DBTime series31%30%29%28%27%SnowflakeApache DruidApache PinotDatabricksClickHouseColumnar/data warehouses33%30%28%27%27%HBaseScyllaDBCassandraAccumuloAmazon KeyspacesWide-column storesPlanning to adop

133、t data management tools by category%of respondents who are using or are planning to use each data management system type(n=497)44ABOUT THE AUTHORSLiam DoddData StorytellerLiam is a researcher with an interest in data analytics and its ability to impact society.He holds a PhD in Physics,and previousl

134、y worked generating intelligence and insights for the European automotive market.Konstantinos KorakitisDirector of ResearchKonstantinos heads the Research Product team at SlashDataand is responsible for all syndicated research products and custom research projects.With more than 10 years of experien

135、ce as an engineer,consultant,and manager,he oversees research planning,survey design,data analysis,insights generation,and research operations.Nikita SolodkovData StorytellerNikita is a multidisciplinary researcher with a particular interest in using data-driven insights to solve real-world problems

136、.He holds a PhD in Physics and has over five years of experience in data analytics and research design.nikita.solodkovslashdata.cokonstantinosslashdata.coliam.doddslashdata.coWHO DEVELOPERS AREWHERE THEY ARE GOINGWHAT THEY BUYDeveloper population sizingDeveloper segmentationWe help the world underst

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