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DBMS > Apache Phoenix vs. CrateDB vs. Hawkular Metrics vs. SiteWhere

System Properties Comparison Apache Phoenix vs. CrateDB vs. Hawkular Metrics vs. SiteWhere

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonCrateDB  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonSiteWhere  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseDistributed Database based on LuceneHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.M2M integration platform for persisting/querying time series data
Primary database modelRelational DBMSDocument store
Spatial DBMS
Search engine
Time Series DBMS
Vector DBMS
Time Series DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.90
Rank#125  Overall
#59  Relational DBMS
Score0.69
Rank#226  Overall
#37  Document stores
#5  Spatial DBMS
#16  Search engines
#19  Time Series DBMS
#11  Vector DBMS
Score0.01
Rank#377  Overall
#39  Time Series DBMS
Score0.07
Rank#347  Overall
#33  Time Series DBMS
Websitephoenix.apache.orgcratedb.comwww.hawkular.orggithub.com/­sitewhere/­sitewhere
Technical documentationphoenix.apache.orgcratedb.com/­docswww.hawkular.org/­hawkular-metrics/­docs/­user-guidesitewhere1.sitewhere.io/­index.html
DeveloperApache Software FoundationCrateCommunity supported by Red HatSiteWhere
Initial release2014201320142010
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20195.8.1, August 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open SourceOpen Source infoApache 2.0Open Source infoCommon Public Attribution License Version 1.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaJavaJava
Server operating systemsLinux
Unix
Windows
All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator supportLinux
OS X
Windows
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesFlexible Schema (defined schema, partial schema, schema free)schema-freepredefined scheme
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.nononono
Secondary indexesyesyesnono
SQL infoSupport of SQLyesyes, but no triggers and constraints, and PostgreSQL compatibilitynono
APIs and other access methodsJDBCADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API
HTTP RESTHTTP REST
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
.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
Go
Java
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsuser defined functions (Javascript)no
Triggersnonoyes infovia Hawkular Alerting
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on CassandraSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Configurable replication on table/partition-levelselectable replication factor infobased on Cassandraselectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyEventual Consistency
Read-after-write consistency on record level
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 dataACIDno infounique row identifiers can be used for implementing an optimistic concurrency control strategynono
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.yesnonono
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyrights management via user accountsnoUsers with fine-grained authorization concept

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More resources
Apache PhoenixCrateDBHawkular MetricsSiteWhere
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