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DBMS > CrateDB vs. GeoSpock vs. OrigoDB vs. Postgres-XL

System Properties Comparison CrateDB vs. GeoSpock vs. OrigoDB vs. Postgres-XL

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonGeoSpock  Xexclude from comparisonOrigoDB  Xexclude from comparisonPostgres-XL  Xexclude from comparison
GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
DescriptionDistributed Database based on LuceneSpatial and temporal data processing engine for extreme data scaleA fully ACID in-memory object graph databaseBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSDocument store
Object oriented DBMS
Relational DBMS
Secondary database modelsRelational DBMSTime Series DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#10  Vector DBMS
Score0.06
Rank#380  Overall
#50  Document stores
#19  Object oriented DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Websitecratedb.comgeospock.comorigodb.comwww.postgres-xl.org
Technical documentationcratedb.com/­docsorigodb.com/­docswww.postgres-xl.org/­documentation
DeveloperCrateGeoSpockRobert Friberg et al
Initial release20132009 infounder the name LiveDB2014 infosince 2012, originally named StormDB
Current release2.0, September 201910 R1, October 2018
License infoCommercial or Open SourceOpen SourcecommercialOpen SourceOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenoyesnono
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 languageJavaJava, JavascriptC#C
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supporthostedLinux
Windows
Linux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyesyesUser defined using .NET types and collectionsyes
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 infocan be achieved using .NETyes infoXML type, but no XML query functionality
Secondary indexesyestemporal, categoricalyesyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilityANSI SQL for query only (using Presto)noyes infodistributed, parallel query execution
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBC.NET Client API
HTTP API
LINQ
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
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
.Net.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresuser defined functions (Javascript)noyesuser defined functions
Triggersnonoyes infoDomain Eventsyes
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic shardinghorizontal partitioning infoclient side managed; servers are not synchronizedhorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelSource-replica replication
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
Foreign keys infoReferential integritynonodepending on modelyes
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 strategynoACIDACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoWrite ahead logyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyesno
User concepts infoAccess controlrights management via user accountsAccess rights for users can be defined per tableRole based authorizationfine grained access rights according to SQL-standard
More information provided by the system vendor
CrateDBGeoSpockOrigoDBPostgres-XL
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
CrateDBGeoSpockOrigoDBPostgres-XL
Recent citations in the news

AWS Marketplace: CrateDB Cloud Comments
12 June 2024, AWS Blog

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8 April 2024, Datanami

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25 March 2024, PR Newswire

How We Designed CrateDB as a Realtime SQL DBMS for the Internet of Things
29 August 2017, The New Stack

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16 May 2017, businesswire.com

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Imagining an 'Everything Connected' World With Geospock | AWS Startups Blog
20 June 2019, AWS Blog

GeoSpock launches Spatial Big Data Platform 2.0
4 September 2019, VanillaPlus

GeoSpock launches pioneering new spatial Big Data platform
27 February 2019, Geospatial World

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