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DBMS > AgensGraph vs. CrateDB vs. JaguarDB vs. LMDB

System Properties Comparison AgensGraph vs. CrateDB vs. JaguarDB vs. LMDB

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Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonCrateDB  Xexclude from comparisonJaguarDB  Xexclude from comparisonLMDB  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLDistributed Database based on LucenePerformant, highly scalable DBMS for AI and IoT applicationsA high performant, light-weight, embedded key-value database library
Primary database modelGraph DBMS
Relational DBMS
Document store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value store
Vector DBMS
Key-value store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.20
Rank#321  Overall
#27  Graph DBMS
#143  Relational DBMS
Score0.73
Rank#224  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#8  Vector DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector DBMS
Score1.99
Rank#125  Overall
#21  Key-value stores
Websitebitnine.net/­agensgraphcratedb.comwww.jaguardb.comwww.symas.com/­symas-embedded-database-lmdb
Technical documentationbitnine.net/­documentationcratedb.com/­docswww.jaguardb.com/­support.htmlwww.lmdb.tech/­doc
DeveloperBitnine Global Inc.CrateDataJaguar, Inc.Symas
Initial release2016201320152011
Current release2.1, December 20183.3 July 20230.9.32, January 2024
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open SourceOpen Source infoGPL V3.0Open Source
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 languageCJavaC++ infothe server part. Clients available in other languagesC
Server operating systemsLinux
OS X
Windows
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinuxLinux
Unix
Windows
Data schemedepending on used data modelFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesyesyes
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
Secondary indexesyesyesyesno
SQL infoSupport of SQLyesyes, but no triggers and constraints, and PostgreSQL compatibilityA subset of ANSI SQL is implemented infobut no views, foreign keys, triggersno
APIs and other access methodsCypher Query Language
JDBC
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JDBC
ODBC
Supported programming languagesC
Java
JavaScript
Python
.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
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
.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
Server-side scripts infoStored proceduresyesuser defined functions (Javascript)nono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritanceShardingShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationConfigurable replication on table/partition-levelMulti-source replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Read-after-write consistency on record level
Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonono
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 strategynoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nononoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardrights management via user accountsrights management via user accountsno
More information provided by the system vendor
AgensGraphCrateDBJaguarDBLMDB
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
AgensGraphCrateDBJaguarDBLMDB
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