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DBMS > CrateDB vs. Ingres vs. LMDB vs. OpenQM

System Properties Comparison CrateDB vs. Ingres vs. LMDB vs. OpenQM

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonIngres  Xexclude from comparisonLMDB  Xexclude from comparisonOpenQM infoalso called QM  Xexclude from comparison
DescriptionDistributed Database based on LuceneWell established RDBMSA high performant, light-weight, embedded key-value database libraryQpenQM is a high-performance, self-tuning, multi-value DBMS
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSKey-value storeMultivalue DBMS
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
Score4.11
Rank#81  Overall
#44  Relational DBMS
Score1.99
Rank#125  Overall
#21  Key-value stores
Score0.27
Rank#298  Overall
#10  Multivalue DBMS
Websitecratedb.comwww.actian.com/­databases/­ingreswww.symas.com/­symas-embedded-database-lmdbwww.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-open-qm
Technical documentationcratedb.com/­docsdocs.actian.com/­ingreswww.lmdb.tech/­doc
DeveloperCrateActian CorporationSymasRocket Software, originally Martin Phillips
Initial release20131974 infooriginally developed at University Berkely in early 1970s20111993
Current release11.2, May 20220.9.32, January 20243.4-12
License infoCommercial or Open SourceOpen SourcecommercialOpen SourceOpen Source infoGPLv2, extended commercial license 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 languageJavaCC
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
Linux
Unix
Windows
AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeyes infowith some exceptions
Typing infopredefined data types such as float or dateyesyes
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.nono infobut tools for importing/exporting data from/to XML-files availablenoyes
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilityyesnono
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)
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++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl
.Net
Basic
C
Java
Objective C
PHP
Python
Server-side scripts infoStored proceduresuser defined functions (Javascript)yesnoyes
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslynoneyes
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelIngres Replicatornoneyes
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
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 strategyACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyesyes
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.nonoyes
User concepts infoAccess controlrights management via user accountsfine grained access rights according to SQL-standardnoAccess rights can be defined down to the item level
More information provided by the system vendor
CrateDBIngresLMDBOpenQM infoalso called QM
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
CrateDBIngresLMDBOpenQM infoalso called QM
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