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

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

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDrizzle  Xexclude from comparisonGridDB  Xexclude from comparisonQuestDB  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.
DescriptionAnalytic DBMS for HadoopMySQL 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 DataA high performance open source SQL database for time series dataA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSRelational DBMSTime Series DBMSTime Series DBMSTime Series DBMS
Secondary database modelsDocument storeKey-value store
Relational DBMS
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websiteimpala.apache.orggriddb.netquestdb.iowww.timescale.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.griddb.netquestdb.io/­docsdocs.timescale.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDrizzle project, originally started by Brian AkerToshiba CorporationQuestDB Technology IncTimescale
Initial release20132008201320142017
Current release4.1.0, June 20227.2.4, September 20125.1, August 20222.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoGNU GPLOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++C++Java (Zero-GC), C++, RustC
Server operating systemsLinuxFreeBSD
Linux
OS X
LinuxLinux
macOS
Windows
Linux
OS X
Windows
Data schemeyesyesyesyes infoschema-free via InfluxDB Line Protocolyes
Typing infopredefined data types such as float or dateyesyesyes 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.nononoyes
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infowith proprietary extensionsSQL92, SQL-like TQL (Toshiba Query Language)SQL with time-series extensionsyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
ODBC
JDBCJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Java
PHP
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenononouser 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.yesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal partitioning (by timestamps)yes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication
Source-replica replication
Source-replica replicationSource-replica replication with eventual consistencySource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID at container levelACID for single-table writesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes infothrough memory mapped filesno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosPluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users can be defined per databasefine grained access rights according to SQL-standard
More information provided by the system vendor
Apache ImpalaDrizzleGridDBQuestDBTimescaleDB
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Relational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Financial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
Apache ImpalaDrizzleGridDBQuestDBTimescaleDB
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