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DBMS > Apache Phoenix vs. Drizzle vs. Quasardb vs. TimescaleDB

System Properties Comparison Apache Phoenix vs. Drizzle vs. Quasardb vs. TimescaleDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonDrizzle  Xexclude from comparisonQuasardb  Xexclude from comparisonTimescaleDB  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.Distributed, high-performance timeseries databaseA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSRelational DBMSTime Series DBMSTime Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.97
Rank#126  Overall
#59  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitephoenix.apache.orgquasar.aiwww.timescale.com
Technical documentationphoenix.apache.orgdoc.quasar.ai/­masterdocs.timescale.com
DeveloperApache Software FoundationDrizzle project, originally started by Brian AkerquasardbTimescale
Initial release2014200820092017
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20197.2.4, September 20123.14.1, January 20242.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoGNU GPLcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen 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++C++C
Server operating systemsLinux
Unix
Windows
FreeBSD
Linux
OS X
BSD
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infointeger and binarynumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.nonoyes
Secondary indexesyesyesyes infowith tagsyes
SQL infoSupport of SQLyesyes infowith proprietary extensionsSQL-like query languageyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBCJDBCHTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C#
C++
Go
Groovy
Java
PHP
Python
Scala
C
C++
Java
PHP
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functionsnonouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnono infohooks for callbacks inside the server can be used.noyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoconsistent hashingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
Source-replica replication with selectable replication factorSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnowith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoTransient modeno
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, HTTPCryptographically strong user authentication and audit trailfine grained access rights according to SQL-standard

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More resources
Apache PhoenixDrizzleQuasardbTimescaleDB
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