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DBMS > AgensGraph vs. BigObject vs. CrateDB vs. Kyligence Enterprise

System Properties Comparison AgensGraph vs. BigObject vs. CrateDB vs. Kyligence Enterprise

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Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonBigObject  Xexclude from comparisonCrateDB  Xexclude from comparisonKyligence Enterprise  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLAnalytic DBMS for real-time computations and queriesDistributed Database based on LuceneA distributed analytics engine for big data, built on top of Apache Kylin
Primary database modelGraph DBMS
Relational DBMS
Relational DBMS infoa hierachical model (tree) can be imposedDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMS
Secondary database modelsRelational 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
Score0.13
Rank#333  Overall
#147  Relational DBMS
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score0.40
Rank#269  Overall
#124  Relational DBMS
Websitebitnine.net/­agensgraphbigobject.iocratedb.comkyligence.io/­kyligence-enterprise
Technical documentationbitnine.net/­documentationdocs.bigobject.iocratedb.com/­docs
DeveloperBitnine Global Inc.BigObject, Inc.CrateKyligence, Inc.
Initial release2016201520132016
Current release2.1, December 2018
License infoCommercial or Open SourceOpen Source infoApache License 2.0commercial infofree community edition availableOpen Sourcecommercial
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 languageCJavaJava
Server operating systemsLinux
OS X
Windows
Linux infodistributed as a docker-image
OS X infodistributed as a docker-image (boot2docker)
Windows infodistributed as a docker-image (boot2docker)
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
Data schemedepending on used data modelyesFlexible Schema (defined schema, partial schema, schema free)yes
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 indexesyesyesyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyes, but no triggers and constraints, and PostgreSQL compatibilityANSI SQL for queries (using Apache Calcite)
APIs and other access methodsCypher Query Language
JDBC
fluentd
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesC
Java
JavaScript
Python
.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
Server-side scripts infoStored proceduresyesLuauser defined functions (Javascript)
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritancenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneConfigurable replication on table/partition-level
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneEventual Consistency
Read-after-write consistency on record level
Immediate Consistency
Foreign keys infoReferential integrityyesyes infoautomatically between fact table and dimension tablesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono infounique row identifiers can be used for implementing an optimistic concurrency control strategy
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/write lock on objects (tables, trees)yesyes
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.noyesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardnorights management via user accounts
More information provided by the system vendor
AgensGraphBigObjectCrateDBKyligence Enterprise
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
AgensGraphBigObjectCrateDBKyligence Enterprise
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