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DBMS > CrateDB vs. Ehcache vs. Hawkular Metrics vs. Hypertable

System Properties Comparison CrateDB vs. Ehcache vs. Hawkular Metrics vs. Hypertable

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Editorial information provided by DB-Engines
NameCrateDB  Xexclude from comparisonEhcache  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonHypertable  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionDistributed Database based on LuceneA widely adopted Java cache with tiered storage optionsHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.An open source BigTable implementation based on distributed file systems such as Hadoop
Primary database modelDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Key-value storeTime Series DBMSWide column store
Secondary database modelsRelational 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
#10  Vector DBMS
Score4.64
Rank#68  Overall
#8  Key-value stores
Score0.08
Rank#366  Overall
#39  Time Series DBMS
Websitecratedb.comwww.ehcache.orgwww.hawkular.org
Technical documentationcratedb.com/­docswww.ehcache.org/­documentationwww.hawkular.org/­hawkular-metrics/­docs/­user-guide
DeveloperCrateTerracotta Inc, owned by Software AGCommunity supported by Red HatHypertable Inc.
Initial release2013200920142009
Current release3.10.0, March 20220.9.8.11, March 2016
License infoCommercial or Open SourceOpen SourceOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0Open Source infoGNU 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 languageJavaJavaJavaC++
Server operating systemsAll Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportAll OS with a Java VMLinux
OS X
Windows
Linux
OS X
Windows infoan inofficial Windows port is available
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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 indexesyesnonorestricted infoonly exact value or prefix value scans
SQL infoSupport of SQLyes, but no triggers and constraints, and PostgreSQL compatibilitynonono
APIs and other access methodsADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
JCacheHTTP RESTC++ API
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
JavaGo
Java
Python
Ruby
C++
Java
Perl
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions (Javascript)nonono
Triggersnoyes infoCache Event Listenersyes infovia Hawkular Alertingno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoby using Terracotta ServerSharding infobased on CassandraSharding
Replication methods infoMethods for redundantly storing data on multiple nodesConfigurable replication on table/partition-levelyes infoby using Terracotta Serverselectable replication factor infobased on Cassandraselectable replication factor on file system level
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Read-after-write consistency on record level
Tunable Consistency (Strong, Eventual, Weak)Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynononono
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 resourcenono
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.noyesno
User concepts infoAccess controlrights management via user accountsnonono
More information provided by the system vendor
CrateDBEhcacheHawkular MetricsHypertable
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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CrateDBEhcacheHawkular MetricsHypertable
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