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DBMS > CrateDB vs. Datomic vs. FeatureBase vs. Warp 10

System Properties Comparison CrateDB vs. Datomic vs. FeatureBase vs. Warp 10

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonDatomic  Xexclude from comparisonFeatureBase  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionDistributed Database based on LuceneDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSRelational DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#10  Vector DBMS
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score0.31
Rank#292  Overall
#135  Relational DBMS
Score0.14
Rank#344  Overall
#32  Time Series DBMS
Websitecratedb.comwww.datomic.comwww.featurebase.comwww.warp10.io
Technical documentationcratedb.com/­docsdocs.datomic.comdocs.featurebase.comwww.warp10.io/­content/­02_Getting_started
DeveloperCrateCognitectMolecula and Pilosa Open Source ContributorsSenX
Initial release2013201220172015
Current release1.0.7075, December 20232022, May 2022
License infoCommercial or Open SourceOpen Sourcecommercial infolimited edition freecommercialOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenononono
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 languageJavaJava, ClojureGoJava
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAll OS with a Java VMLinux
macOS
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes
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.nononono
Secondary indexesyesyesnono
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitynoSQL queriesno
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
RESTful HTTP APIgRPC
JDBC
Kafka Connector
ODBC
HTTP API
Jupyter
WebSocket
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
Clojure
Java
Java
Python
Server-side scripts infoStored proceduresuser defined functions (Javascript)yes infoTransaction Functionsyes infoWarpScript
TriggersnoBy using transaction functionsnono
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peersShardingSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelnone infoBut extensive use of caching in the application peersyesselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynonoyesno
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 strategyACIDyesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes, using Linux fsyncyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentyesyes
User concepts infoAccess controlrights management via user accountsnoMandatory use of cryptographic tokens, containing fine-grained authorizations
More information provided by the system vendor
CrateDBDatomicFeatureBaseWarp 10
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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CrateDBDatomicFeatureBaseWarp 10
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