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DBMS > Drizzle vs. Impala vs. Quasardb vs. TimescaleDB

System Properties Comparison Drizzle vs. Impala vs. Quasardb vs. TimescaleDB

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonImpala  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.
DescriptionMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Analytic DBMS for HadoopDistributed, 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 modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.93
Rank#38  Overall
#23  Relational DBMS
Score0.14
Rank#300  Overall
#25  Time Series DBMS
Score4.33
Rank#84  Overall
#5  Time Series DBMS
Websitewww.cloudera.com/­products/­open-source/­apache-hadoop/­impala.htmlquasardb.netwww.timescale.com
Technical documentationdocs.cloudera.com/­documentation/­enterprise/­latest/­topics/­impala.htmldoc.quasardb.netdocs.timescale.com
DeveloperDrizzle project, originally started by Brian AkerClouderaquasardbTimescale
Initial release2008201320092017
Current release7.2.4, September 20123.4.0, April 20203.1, January 2019
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoApache Version 2commercial 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

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++C++C
Server operating systemsFreeBSD
Linux
OS X
LinuxBSD
Linux
OS X
Windows
Linux
OS X
Windows
Data schemeyesyesschema-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 SQLyes infowith proprietary extensionsSQL-like DML and DDL statementsSQL-like query languageyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBCJDBC
ODBC
HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C++
Java
PHP
All languages supporting JDBC/ODBC.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 proceduresnoyes infouser defined functions and integration of map-reducenouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersno infohooks for callbacks inside the server can be used.nonoyes
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
selectable replication factorSource-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 methodsnoyes infoquery execution via MapReducewith Hadoop integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
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.noyes infoTransient modeno
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles infobased on Apache Sentry and KerberosCryptographically strong user authentication and audit trailfine grained access rights according to SQL-standard
More information provided by the system vendor
DrizzleImpalaQuasardbTimescaleDB
Specific characteristicsHigh-performance , high-speed, fully integrated timeseries database Seamlessly combines...
» more
Competitive advantagesHigh performance in a cost-effective small package Real-time results for even large...
» more
Typical application scenariosTick database Predictive maintenance Pre-deal checks Large scale monitoring
» more
Key customersLarge EU investment banks US based hedge funds Orolia Tellmeplus
» more
Market metricsHas been running in very demanding production environments since 2013 Rapid adoption...
» more
Licensing and pricing modelsCommunity edition limited to 2 nodes and 16 GiB of storage per node available for...
» more

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More resources
DrizzleImpalaQuasardbTimescaleDB
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Recent citations in the news

Cloudera’s Impala brings Hadoop to SQL and BI
25 October 2012, ZDNet

Man Busts Out of Google, Rebuilds Top-Secret Query Machine
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29 June 2017, insideBIGDATA

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2 October 2020, TechTarget

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11 August 2021, CDOTrends

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Timescale scales out and sets its sights on analytics
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