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DBMS > ArcadeDB vs. CrateDB vs. EXASOL vs. Ingres

System Properties Comparison ArcadeDB vs. CrateDB vs. EXASOL vs. Ingres

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Editorial information provided by DB-Engines
NameArcadeDB  Xexclude from comparisonCrateDB  Xexclude from comparisonEXASOL  Xexclude from comparisonIngres  Xexclude from comparison
DescriptionFast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewrittenDistributed Database based on LuceneHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Well established RDBMS
Primary database modelDocument store
Graph DBMS
Key-value store
Time Series DBMS infoin next version
Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSRelational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.10
Rank#358  Overall
#48  Document stores
#38  Graph DBMS
#52  Key-value stores
#35  Time Series DBMS
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score3.80
Rank#82  Overall
#44  Relational DBMS
Websitearcadedb.comcratedb.comwww.exasol.comwww.actian.com/­databases/­ingres
Technical documentationdocs.arcadedb.comcratedb.com/­docswww.exasol.com/­resourcesdocs.actian.com/­ingres
DeveloperArcade DataCrateExasolActian Corporation
Initial release2021201320001974 infooriginally developed at University Berkely in early 1970s
Current releaseSeptember 202111.2, May 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Sourcecommercialcommercial
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
Server operating systemsAll OS with a Java VMAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesyes
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 infobut tools for importing/exporting data from/to XML-files available
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like query language, no joinsyes, but no triggers and constraints, and PostgreSQL compatibilityyesyes
APIs and other access methodsJDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
.Net
JDBC
ODBC
WebSocket
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Supported programming languagesJava.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
Java
Lua
Python
R
Server-side scripts infoStored proceduresuser defined functions (Javascript)user defined functionsyes
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneously
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationConfigurable replication on table/partition-levelIngres Replicator
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoHadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes inforelationship in graphsnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDno infounique row identifiers can be used for implementing an optimistic concurrency control strategyACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMVCC
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.noyesno
User concepts infoAccess controlrights management via user accountsAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard
More information provided by the system vendor
ArcadeDBCrateDBEXASOLIngres
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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ArcadeDBCrateDBEXASOLIngres
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