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DBMS > AgensGraph vs. FeatureBase vs. Kinetica

System Properties Comparison AgensGraph vs. FeatureBase vs. Kinetica

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Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonFeatureBase  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Fully vectorized database across both GPUs and CPUs
Primary database modelGraph DBMS
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#322  Overall
#30  Graph DBMS
#143  Relational DBMS
Score0.22
Rank#305  Overall
#138  Relational DBMS
Score0.44
Rank#256  Overall
#118  Relational DBMS
Websitebitnine.net/­agensgraphwww.featurebase.comwww.kinetica.com
Technical documentationbitnine.net/­documentationdocs.featurebase.comdocs.kinetica.com
DeveloperBitnine Global Inc.Molecula and Pilosa Open Source ContributorsKinetica
Initial release201620172012
Current release2.1, December 20182022, May 20227.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCGoC, C++
Server operating systemsLinux
OS X
Windows
Linux
macOS
Linux
Data schemedepending on used data modelyesyes
Typing infopredefined data types such as float or dateyesyesyes
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
Secondary indexesyesnoyes
SQL infoSupport of SQLyesSQL queriesSQL-like DML and DDL statements
APIs and other access methodsCypher Query Language
JDBC
gRPC
JDBC
Kafka Connector
ODBC
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
Java
JavaScript
Python
Java
Python
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesuser defined functions
Triggersnonoyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes, using Linux fsyncyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoGPU vRAM or System RAM
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users and roles on table level

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More resources
AgensGraphFeatureBaseKinetica
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