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DBMS > Drizzle vs. GridDB vs. Impala vs. TimescaleDB

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

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Editorial information provided by DB-Engines
NameDrizzle  Xexclude from comparisonGridDB  Xexclude from comparisonImpala  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.Scalable in-memory time series database optimized for IoT and Big DataAnalytic DBMS for HadoopA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSTime Series DBMSRelational DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
Document storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.24
Rank#155  Overall
#12  Time Series DBMS
Score17.49
Rank#40  Overall
#25  Relational DBMS
Score4.52
Rank#83  Overall
#5  Time Series DBMS
Websitegriddb.netwww.cloudera.com/­products/­open-source/­apache-hadoop/­impala.htmlwww.timescale.com
Technical documentationdocs.griddb.netdocs.cloudera.com/­documentation/­enterprise/­latest/­topics/­impala.htmldocs.timescale.com
DeveloperDrizzle project, originally started by Brian AkerToshiba CorporationClouderaTimescale
Initial release2008201320132017
Current release7.2.4, September 20124.6, February 20214.0.0, July 20212.6.0, February 2022
License infoCommercial or Open SourceOpen Source infoGNU GPLOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2Open 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 languageC++C++C++C
Server operating systemsFreeBSD
Linux
OS X
LinuxLinuxLinux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampyesnumerics, 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 indexesyesyesyesyes
SQL infoSupport of SQLyes infowith proprietary extensionsSQL92, SQL-like TQL (Toshiba Query Language)SQL-like DML and DDL statementsyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBCProprietary protocolJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC
C++
Java
PHP
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnonoyes infouser defined functions and integration of map-reduceuser 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.yesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replicationselectable replication factorSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes infoquery execution via MapReduceno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelnoACID
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.yesnono
User concepts infoAccess controlPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users can be defined per databaseAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standard
More information provided by the system vendor
DrizzleGridDBImpalaTimescaleDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
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Timescale is the creator of TimescaleDB , the first open-source relational database...
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Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
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TimescaleDB is purpose-built to scale and handle time-series data workloads and is...
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Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Time-series Analytics TimescaleDB boosts the performance of PostgreSQL for time-series...
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Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
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TransferWise, Maersk, Walmart, Comcast, LaunchDarkly, IBM, NOV, Cisco, Nutanix, Warner...
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Market metricsGitHub trending repository
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With over 12,700 GitHub stars and growing, 1,000,000 active databases, and an active...
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Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
TimescaleDB is available as a self-hosted product under two licenses, the Timescale...
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DrizzleGridDBImpalaTimescaleDB
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