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DBMS > CrateDB vs. EXASOL vs. Solr vs. TigerGraph

System Properties Comparison CrateDB vs. EXASOL vs. Solr vs. TigerGraph

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonEXASOL  Xexclude from comparisonSolr  Xexclude from comparisonTigerGraph  Xexclude from comparison
DescriptionDistributed Database based on LuceneHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.A widely used distributed, scalable search engine based on Apache LuceneA complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSSearch engineGraph DBMS
Secondary database modelsRelational DBMSSpatial 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
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Score1.83
Rank#139  Overall
#13  Graph DBMS
Websitecratedb.comwww.exasol.comsolr.apache.orgwww.tigergraph.com
Technical documentationcratedb.com/­docswww.exasol.com/­resourcessolr.apache.org/­resources.htmldocs.tigergraph.com
DeveloperCrateExasolApache Software Foundation
Initial release2013200020062017
Current release9.6.0, April 2024
License infoCommercial or Open SourceOpen SourcecommercialOpen Source infoApache Version 2commercial
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 languageJavaJavaC++
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes infoDynamic Fields enables on-the-fly addition of new fieldsyes
Typing infopredefined data types such as float or dateyesyesyes infosupports customizable data types and automatic typingyes
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.nonoyesno
Secondary indexesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilityyesSolr Parallel SQL InterfaceSQL-like query language (GSQL)
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
.Net
JDBC
ODBC
WebSocket
Java API
RESTful HTTP/JSON API
GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON 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
Java
Lua
Python
R
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
C++
Java
Server-side scripts infoStored proceduresuser defined functions (Javascript)user defined functionsJava pluginsyes
Triggersnoyesyes infoUser configurable commands triggered on index changesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyesnoyes infoRelationships in graphs
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 strategyACIDoptimistic lockingACID
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.noyesyesno
User concepts infoAccess controlrights management via user accountsAccess rights for users, groups and roles according to SQL-standardyesRole-based access control
More information provided by the system vendor
CrateDBEXASOLSolrTigerGraph
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
CrateDBEXASOLSolrTigerGraph
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