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DBMS > CrateDB vs. GeoMesa vs. Ingres vs. Sphinx

System Properties Comparison CrateDB vs. GeoMesa vs. Ingres vs. Sphinx

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonGeoMesa  Xexclude from comparisonIngres  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionDistributed Database based on LuceneGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Well established RDBMSOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Spatial DBMSRelational DBMSSearch engine
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score0.78
Rank#213  Overall
#4  Spatial DBMS
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websitecratedb.comwww.geomesa.orgwww.actian.com/­databases/­ingressphinxsearch.com
Technical documentationcratedb.com/­docswww.geomesa.org/­documentation/­stable/­user/­index.htmldocs.actian.com/­ingressphinxsearch.com/­docs
DeveloperCrateCCRi and othersActian CorporationSphinx Technologies Inc.
Initial release201320141974 infooriginally developed at University Berkely in early 1970s2001
Current release5.0.0, May 202411.2, May 20223.5.1, February 2023
License infoCommercial or Open SourceOpen SourceOpen Source infoApache License 2.0commercialOpen Source infoGPL version 2, commercial licence available
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 languageJavaScalaCC++
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesyes
Typing infopredefined data types such as float or dateyesyesyesno
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 infobut tools for importing/exporting data from/to XML-files available
Secondary indexesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitynoyesSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Proprietary protocol
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
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions (Javascript)noyesno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingdepending on storage layerhorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-leveldepending on storage layerIngres Replicatornone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
depending on storage layerImmediate Consistency
Foreign keys infoReferential integritynonoyesno
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 strategynoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nodepending on storage layerno
User concepts infoAccess controlrights management via user accountsyes infodepending on the DBMS used for storagefine grained access rights according to SQL-standardno
More information provided by the system vendor
CrateDBGeoMesaIngresSphinx
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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CrateDBGeoMesaIngresSphinx
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