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DBMS > CrateDB vs. Hazelcast vs. InterSystems Caché vs. SWC-DB

System Properties Comparison CrateDB vs. Hazelcast vs. InterSystems Caché vs. SWC-DB

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonHazelcast  Xexclude from comparisonInterSystems Caché  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.
DescriptionDistributed Database based on LuceneA widely adopted in-memory data gridA multi-model DBMS and application serverA high performance, scalable Wide Column DBMS
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value storeKey-value store
Object oriented DBMS
Relational DBMS
Wide column store
Secondary database modelsRelational DBMSDocument store infoJSON support with IMDG 3.12Document storeTime 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
#8  Vector DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.08
Rank#364  Overall
#13  Wide column stores
Websitecratedb.comhazelcast.comwww.intersystems.com/­products/­cachegithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationcratedb.com/­docshazelcast.org/­imdg/­docsdocs.intersystems.com
DeveloperCrateHazelcastInterSystemsAlex Kashirin
Initial release2013200819972020
Current release5.3.6, November 20232018.1.4, May 20200.5, April 2021
License infoCommercial or Open SourceOpen SourceOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoGPL V3
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 VMAIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freedepending on used data modelschema-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.noyes infothe object must implement a serialization strategyyesno
Secondary indexesyesyesyes
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitySQL-like query languageyesSQL-like query language
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
.NET Client API
JDBC
ODBC
RESTful HTTP API
Proprietary protocol
Thrift
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
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C#
C++
Java
C++
Server-side scripts infoStored proceduresuser defined functions (Javascript)yes infoEvent Listeners, Executor Servicesyesno
Triggersnoyes infoEventsyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelyes infoReplicated MapSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Immediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
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 strategyone or two-phase-commit; repeatable reads; read commitedACID
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 accountsRole-based access controlAccess rights for users, groups and roles
More information provided by the system vendor
CrateDBHazelcastInterSystems CachéSWC-DB infoSuper Wide Column Database
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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CrateDBHazelcastInterSystems CachéSWC-DB infoSuper Wide Column Database
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