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DBMS > Apache Phoenix vs. Drizzle vs. GigaSpaces vs. Prometheus

System Properties Comparison Apache Phoenix vs. Drizzle vs. GigaSpaces vs. Prometheus

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDrizzle  Xexclude from comparisonGigaSpaces  Xexclude from comparisonPrometheus  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsOpen-source Time Series DBMS and monitoring system
Primary database modelRelational DBMSRelational DBMSDocument store
Object oriented DBMS infoValues are user defined objects
Time Series DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.06
Rank#123  Overall
#58  Relational DBMS
Score1.03
Rank#188  Overall
#32  Document stores
#6  Object oriented DBMS
Score7.69
Rank#50  Overall
#3  Time Series DBMS
Websitephoenix.apache.orgwww.gigaspaces.comprometheus.io
Technical documentationphoenix.apache.orgdocs.gigaspaces.com/­latest/­landing.htmlprometheus.io/­docs
DeveloperApache Software FoundationDrizzle project, originally started by Brian AkerGigaspaces Technologies
Initial release2014200820002015
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20197.2.4, September 201215.5, September 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGNU GPLOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++Java, C++, .NetGo
Server operating systemsLinux
Unix
Windows
FreeBSD
Linux
OS X
Linux
macOS
Solaris
Windows
Linux
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesNumeric data only
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.nono infoXML can be used for describing objects metadatano infoImport of XML data possible
Secondary indexesyesyesyesno
SQL infoSupport of SQLyesyes infowith proprietary extensionsSQL-99 for query and DML statementsno
APIs and other access methodsJDBCJDBCGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C++
Java
PHP
.Net
C++
Java
Python
Scala
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsnoyesno
Triggersnono infohooks for callbacks inside the server can be used.yes, event driven architectureno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
Multi-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyes infoMap-Reduce pattern can be built with XAP task executorsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYnone
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDno
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.yesyesno
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyPluggable authentication mechanisms infoe.g. LDAP, HTTPRole-based access controlno

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Apache PhoenixDrizzleGigaSpacesPrometheus
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