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DBMS > CrateDB vs. GeoMesa vs. Ingres vs. Quasardb

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

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonGeoMesa  Xexclude from comparisonIngres  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionDistributed Database based on LuceneGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.Well established RDBMSDistributed, high-performance timeseries database
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Spatial DBMSRelational DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.76
Rank#226  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#18  Time Series DBMS
#8  Vector DBMS
Score0.82
Rank#218  Overall
#4  Spatial DBMS
Score5.15
Rank#74  Overall
#40  Relational DBMS
Score0.19
Rank#330  Overall
#30  Time Series DBMS
Websitecratedb.comwww.geomesa.orgwww.actian.com/­databases/­ingresquasar.ai
Technical documentationcratedb.com/­docswww.geomesa.org/­documentation/­stable/­user/­index.htmldocs.actian.com/­ingresdoc.quasar.ai/­master
DeveloperCrateCCRi and othersActian Corporationquasardb
Initial release201320141974 infooriginally developed at University Berkely in early 1970s2009
Current release4.0.5, February 202411.2, May 20223.14.1, January 2024
License infoCommercial or Open SourceOpen SourceOpen Source infoApache License 2.0commercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
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
BSD
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes infointeger and binary
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 availableno
Secondary indexesyesyesyesyes infowith tags
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitynoyesSQL-like query language
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)
HTTP API
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
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
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 infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-leveldepending on storage layerIngres ReplicatorSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
depending on storage layerImmediate ConsistencyImmediate 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 strategynoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes infoMVCCyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nodepending on storage layernoyes infoTransient mode
User concepts infoAccess controlrights management via user accountsyes infodepending on the DBMS used for storagefine grained access rights according to SQL-standardCryptographically strong user authentication and audit trail
More information provided by the system vendor
CrateDBGeoMesaIngresQuasardb
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
CrateDBGeoMesaIngresQuasardb
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