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DBMS > AgensGraph vs. BaseX vs. CrateDB vs. LevelDB

System Properties Comparison AgensGraph vs. BaseX vs. CrateDB vs. LevelDB

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Editorial information provided by DB-Engines
NameAgensGraph  Xexclude from comparisonBaseX  Xexclude from comparisonCrateDB  Xexclude from comparisonLevelDB  Xexclude from comparison
DescriptionMulti-model database supporting relational and graph data models and built upon PostgreSQLLight-weight Native XML DBMS with support for XQuery 3.0 and interactive GUI.Distributed Database based on LuceneEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string values
Primary database modelGraph DBMS
Relational DBMS
Native XML DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value store
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.23
Rank#315  Overall
#26  Graph DBMS
#140  Relational DBMS
Score1.84
Rank#135  Overall
#4  Native XML DBMS
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#9  Vector DBMS
Score2.25
Rank#115  Overall
#19  Key-value stores
Websitebitnine.net/­agensgraphbasex.orgcratedb.comgithub.com/­google/­leveldb
Technical documentationbitnine.net/­documentationdocs.basex.orgcratedb.com/­docsgithub.com/­google/­leveldb/­blob/­main/­doc/­index.md
DeveloperBitnine Global Inc.BaseX GmbHCrateGoogle
Initial release2016200720132011
Current release2.1, December 201811.0, June 20241.23, February 2021
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open Source infoBSD licenseOpen SourceOpen Source infoBSD
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 languageCJavaJavaC++
Server operating systemsLinux
OS X
Windows
Linux
OS X
Windows
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportIllumos
Linux
OS X
Windows
Data schemedepending on used data modelschema-freeFlexible Schema (defined schema, partial schema, schema free)schema-free
Typing infopredefined data types such as float or dateyesno infoXQuery supports typesyesno
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
Secondary indexesyesyesyesno
SQL infoSupport of SQLyesnoyes, but no triggers and constraints, and PostgreSQL compatibilityno
APIs and other access methodsCypher Query Language
JDBC
Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ
ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
Supported programming languagesC
Java
JavaScript
Python
Actionscript
C
C#
Haskell
Java
JavaScript infoNode.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic
.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++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
Server-side scripts infoStored proceduresyesyesuser defined functions (Javascript)no
Triggersnoyes infovia eventsnono
Partitioning methods infoMethods for storing different data on different nodesno, but can be realized using table inheritancenoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneConfigurable replication on table/partition-levelnone
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
Immediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDmultiple readers, single writerno infounique row identifiers can be used for implementing an optimistic concurrency control strategyno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infowith automatic compression on writes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlfine grained access rights according to SQL-standardUsers with fine-grained authorization concept on 4 levelsrights management via user accountsno
More information provided by the system vendor
AgensGraphBaseXCrateDBLevelDB
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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