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DBMS > CrateDB vs. Ehcache vs. EXASOL vs. Hazelcast

System Properties Comparison CrateDB vs. Ehcache vs. EXASOL vs. Hazelcast

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonEhcache  Xexclude from comparisonEXASOL  Xexclude from comparisonHazelcast  Xexclude from comparison
DescriptionDistributed Database based on LuceneA widely adopted Java cache with tiered storage optionsHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.A widely adopted in-memory data grid
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value storeRelational DBMSKey-value store
Secondary database modelsRelational DBMSDocument store infoJSON support with IMDG 3.12
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
Score4.64
Rank#68  Overall
#8  Key-value stores
Score1.76
Rank#139  Overall
#62  Relational DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Websitecratedb.comwww.ehcache.orgwww.exasol.comhazelcast.com
Technical documentationcratedb.com/­docswww.ehcache.org/­documentationwww.exasol.com/­resourceshazelcast.org/­imdg/­docs
DeveloperCrateTerracotta Inc, owned by Software AGExasolHazelcast
Initial release2013200920002008
Current release3.10.0, March 20225.3.6, November 2023
License infoCommercial or Open SourceOpen SourceOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoApache Version 2; commercial licenses 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 languageJavaJavaJava
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAll OS with a Java VMAll OS with a Java VM
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes
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.nononoyes infothe object must implement a serialization strategy
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitynoyesSQL-like query language
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JCache.Net
JDBC
ODBC
WebSocket
JCache
JPA
Memcached protocol
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
JavaJava
Lua
Python
R
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresuser defined functions (Javascript)nouser defined functionsyes infoEvent Listeners, Executor Services
Triggersnoyes infoCache Event Listenersyesyes infoEvents
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoby using Terracotta ServerShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelyes infoby using Terracotta Serveryes infoReplicated Map
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infoHadoop integrationyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Tunable Consistency (Strong, Eventual, Weak)Immediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integritynonoyesno
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 strategyyes infosupports JTA and can work as an XA resourceACIDone or two-phase-commit; repeatable reads; read commited
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing a tiered cache-storage approachyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyesyes
User concepts infoAccess controlrights management via user accountsnoAccess rights for users, groups and roles according to SQL-standardRole-based access control
More information provided by the system vendor
CrateDBEhcacheEXASOLHazelcast
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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CrateDBEhcacheEXASOLHazelcast
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