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DBMS > CrateDB vs. EXASOL vs. Quasardb vs. RavenDB

System Properties Comparison CrateDB vs. EXASOL vs. Quasardb vs. RavenDB

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonEXASOL  Xexclude from comparisonQuasardb  Xexclude from comparisonRavenDB  Xexclude from comparison
DescriptionDistributed Database based on LuceneHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Distributed, high-performance timeseries databaseOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Relational DBMSTime Series DBMSDocument store
Secondary database modelsRelational DBMSGraph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.71
Rank#227  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#9  Vector DBMS
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Score2.84
Rank#101  Overall
#18  Document stores
Websitecratedb.comwww.exasol.comquasar.airavendb.net
Technical documentationcratedb.com/­docswww.exasol.com/­resourcesdoc.quasar.ai/­masterravendb.net/­docs
DeveloperCrateExasolquasardbHibernating Rhinos
Initial release2013200020092010
Current release3.14.1, January 20245.4, July 2022
License infoCommercial or Open SourceOpen Sourcecommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoAGPL version 3, 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 languageJavaC++C#
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportBSD
Linux
OS X
Windows
Linux
macOS
Raspberry Pi
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyes infointeger and binaryno
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 indexesyesyesyes infowith tagsyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilityyesSQL-like query languageSQL-like query language (RQL)
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
.Net
JDBC
ODBC
WebSocket
HTTP API.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful 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
Java
Lua
Python
R
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions (Javascript)user defined functionsnoyes
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoconsistent hashingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelSource-replica replication with selectable replication factorMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoHadoop integrationwith Hadoop integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate ConsistencyImmediate ConsistencyDefault ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
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, Cluster-wide transaction available
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infoTransient mode
User concepts infoAccess controlrights management via user accountsAccess rights for users, groups and roles according to SQL-standardCryptographically strong user authentication and audit trailAuthorization levels configured per client per database
More information provided by the system vendor
CrateDBEXASOLQuasardbRavenDB
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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CrateDBEXASOLQuasardbRavenDB
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