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DBMS > CrateDB vs. IBM Db2 Event Store vs. Rockset vs. Yanza

System Properties Comparison CrateDB vs. IBM Db2 Event Store vs. Rockset vs. Yanza

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonIBM Db2 Event Store  Xexclude from comparisonRockset  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionDistributed Database based on LuceneDistributed Event Store optimized for Internet of Things use casesA scalable, reliable search and analytics service in the cloud, built on RocksDBTime Series DBMS for IoT Applications
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Event Store
Time Series DBMS
Document storeTime Series DBMS
Secondary database modelsRelational DBMSRelational DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score0.19
Rank#323  Overall
#2  Event Stores
#28  Time Series DBMS
Score0.79
Rank#211  Overall
#35  Document stores
Websitecratedb.comwww.ibm.com/­products/­db2-event-storerockset.comyanza.com
Technical documentationcratedb.com/­docswww.ibm.com/­docs/­en/­db2-event-storedocs.rockset.com
DeveloperCrateIBMRocksetYanza
Initial release2013201720192015
Current release2.0
License infoCommercial or Open SourceOpen Sourcecommercial infofree developer edition availablecommercialcommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonoyesno infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
CrateDB Cloud: a distributed SQL database that spreads data and processing across an elastic cluster of shared nothing nodes. CrateDB Cloud enables data insights at scale on Microsoft Azure, AWS and Google Cloud Platform.
Implementation languageJavaC and C++C++
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux infoLinux, macOS, Windows for the developer additionhostedWindows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesdynamic typingno
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.nonono infoingestion from XML files supportedno
Secondary indexesyesnoall fields are automatically indexedno
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilityyes infothrough the embedded Spark runtimeRead-only SQL queries, including JOINsno
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API
HTTP RESTHTTP API
Supported programming languages.NET
Erlang
Go infocommunity maintained client
Java
JavaScript (Node.js) infocommunity maintained client
Perl infocommunity maintained client
PHP
Python
R
Ruby infocommunity maintained client
Scala infocommunity maintained client
C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic
Go
Java
JavaScript (Node.js)
Python
any language that supports HTTP calls
Server-side scripts infoStored proceduresuser defined functions (Javascript)yesnono
Triggersnononoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingShardingAutomatic shardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelActive-active shard replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Eventual ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infounique row identifiers can be used for implementing an optimistic concurrency control strategynonono
Concurrency infoSupport for concurrent manipulation of datayesNo - written data is immutableyesyes
Durability infoSupport for making data persistentyesYes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlrights management via user accountsfine grained access rights according to SQL-standardAccess rights for users and organizations can be defined via Rockset consoleno
More information provided by the system vendor
CrateDBIBM Db2 Event StoreRocksetYanza
Specific characteristicsThe enterprise database for time series, documents, and vectors. Distributed - Native...
» more
Competitive advantagesResponse time in milliseconds: e ven for complex ad-hoc queries. Massive scaling...
» more
Typical application scenarios​ IoT: accelerate your IIoT projects with CrateDB, delivering real-time analytics...
» more
Key customersAcross all continents, CrateDB is used by companies of all sizes to meet the most...
» more
Market metricsThe CrateDB open source project was started in 2013 Honorable Mention in 2021 Gartner®...
» more
Licensing and pricing modelsSee CrateDB pricing >
» more

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More resources
CrateDBIBM Db2 Event StoreRocksetYanza
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