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DBMS > CrateDB vs. H2 vs. Kinetica vs. TinkerGraph

System Properties Comparison CrateDB vs. H2 vs. Kinetica vs. TinkerGraph

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonH2  Xexclude from comparisonKinetica  Xexclude from comparisonTinkerGraph  Xexclude from comparison
DescriptionDistributed Database based on LuceneFull-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.Fully vectorized database across both GPUs and CPUsA lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSRelational DBMSGraph DBMS
Secondary database modelsRelational DBMSSpatial DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.73
Rank#229  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score8.22
Rank#50  Overall
#32  Relational DBMS
Score0.69
Rank#234  Overall
#107  Relational DBMS
Score0.12
Rank#344  Overall
#34  Graph DBMS
Websitecratedb.comwww.h2database.comwww.kinetica.comtinkerpop.apache.org/­docs/­current/­reference/­#tinkergraph-gremlin
Technical documentationcratedb.com/­docswww.h2database.com/­html/­main.htmldocs.kinetica.com
DeveloperCrateThomas MuellerKinetica
Initial release2013200520122009
Current release2.2.220, July 20237.1, August 2021
License infoCommercial or Open SourceOpen SourceOpen Source infodual-licence (Mozilla public license, Eclipse public license)commercialOpen Source infoApache 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 languageJavaJavaC, C++Java
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAll OS with a Java VMLinux
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 indexesyesyesyesno
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilityyesSQL-like DML and DDL statementsno
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
TinkerPop 3
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
JavaC++
Java
JavaScript (Node.js)
Python
Groovy
Java
Server-side scripts infoStored proceduresuser defined functions (Javascript)Java Stored Procedures and User-Defined Functionsuser defined functionsno
Triggersnoyesyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelWith clustering: 2 database servers on different computers operate on identical copies of a databaseSource-replica replicationnone
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
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationnone
Foreign keys infoReferential integritynoyesyesyes infoRelationships in graphs
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 strategyACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesno
Durability infoSupport for making data persistentyesyesyesoptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlrights management via user accountsfine grained access rights according to SQL-standardAccess rights for users and roles on table levelno
More information provided by the system vendor
CrateDBH2KineticaTinkerGraph
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
CrateDBH2KineticaTinkerGraph
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