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DBMS > AgensGraph vs. EXASOL vs. GridDB vs. Riak KV

System Properties Comparison AgensGraph vs. EXASOL vs. GridDB vs. Riak KV

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Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonEXASOL  Xexclude from comparisonGridDB  Xexclude from comparisonRiak KV  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Scalable in-memory time series database optimized for IoT and Big DataDistributed, fault tolerant key-value store
Primary database modelGraph DBMS
Relational DBMS
Relational DBMSTime Series DBMSKey-value store infowith links between data sets and object tags for the creation of secondary indexes
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#321  Overall
#27  Graph DBMS
#143  Relational DBMS
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score4.10
Rank#82  Overall
#9  Key-value stores
Websitebitnine.net/­agensgraphwww.exasol.comgriddb.net
Technical documentationbitnine.net/­documentationwww.exasol.com/­resourcesdocs.griddb.netwww.tiot.jp/­riak-docs/­riak/­kv/­latest
DeveloperBitnine Global Inc.ExasolToshiba CorporationOpenSource, formerly Basho Technologies
Initial release2016200020132009
Current release2.1, December 20185.1, August 20223.2.0, December 2022
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache version 2, commercial enterprise edition
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.
Implementation languageCC++Erlang
Server operating systemsLinux
OS X
Windows
LinuxLinux
OS X
Data schemedepending on used data modelyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyes infonumerical, string, blob, geometry, boolean, timestampno
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 indexesyesyesyesrestricted
SQL infoSupport of SQLyesyesSQL92, SQL-like TQL (Toshiba Query Language)no
APIs and other access methodsCypher Query Language
JDBC
.Net
JDBC
ODBC
WebSocket
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP API
Native Erlang Interface
Supported programming languagesC
Java
JavaScript
Python
Java
Lua
Python
R
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
Server-side scripts infoStored proceduresyesuser defined functionsnoErlang
Triggersnoyesyesyes infopre-commit hooks and post-commit hooks
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceShardingShardingSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate consistency within container, eventual consistency across containersEventual Consistency
Foreign keys infoReferential integrityyesyesnono infolinks between data sets can be stored
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID at container levelno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardAccess rights for users can be defined per databaseyes, using Riak Security
More information provided by the system vendor
AgensGraphEXASOLGridDBRiak KV
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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More resources
AgensGraphEXASOLGridDBRiak KV
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