DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache Impala vs. Hawkular Metrics vs. Infobright vs. TimescaleDB vs. Vitess

System Properties Comparison Apache Impala vs. Hawkular Metrics vs. Infobright vs. TimescaleDB vs. Vitess

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonInfobright  Xexclude from comparisonTimescaleDB  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopHawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontendA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSTime Series DBMSRelational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument storeRelational DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.96
Rank#194  Overall
#91  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websiteimpala.apache.orgwww.hawkular.orgignitetech.com/­softwarelibrary/­infobrightdbwww.timescale.comvitess.io
Technical documentationimpala.apache.org/­impala-docs.htmlwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.timescale.comvitess.io/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCommunity supported by Red HatIgnite Technologies Inc.; formerly InfoBright Inc.TimescaleThe Linux Foundation, PlanetScale
Initial release20132014200520172013
Current release4.1.0, June 20222.15.0, May 202415.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0commercial infoThe open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016Open Source infoApache 2.0Open Source infoApache Version 2.0, commercial licenses available
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++JavaCCGo
Server operating systemsLinuxLinux
OS X
Windows
Linux
Windows
Linux
OS X
Windows
Docker
Linux
macOS
Data schemeyesschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyes
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 indexesyesnono infoKnowledge Grid Technology used insteadyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesyes infofull PostgreSQL SQL syntaxyes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
HTTP RESTADO.NET
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCGo
Java
Python
Ruby
.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes infoproprietary syntax
Triggersnoyes infovia Hawkular Alertingnoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on Cassandranoneyes, across time and space (hash partitioning) attributesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorselectable replication factor infobased on CassandraSource-replica replicationSource-replica replication with hot standby and reads on replicas infoMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynononoyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACIDACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes infotable locks or row locks depending on storage engine
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.nonoyesnoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnofine grained access rights according to SQL-standard infoexploiting MySQL or PostgreSQL frontend capabilitiesfine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Apache ImpalaHawkular MetricsInfobrightTimescaleDBVitess
Recent citations in the news

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

Updates & Upserts in Hadoop Ecosystem with Apache Kudu
27 October 2017, KDnuggets

provided by Google News

Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived… • DEVCLASS
5 June 2019, DevClass

provided by Google News

TimescaleDB Is a Vector Database Now, Too
25 September 2023, Datanami

Timescale Acquires PopSQL to Bring a Modern, Collaborative SQL GUI to PostgreSQL Developers
4 April 2024, PR Newswire

Power IoT and time-series workloads with TimescaleDB for Azure Database for PostgreSQL
18 March 2019, Microsoft

Timescale Valuation Rockets to Over $1B with $110M Round, Marking the Explosive Rise of Time-Series Data
22 February 2022, Business Wire

Visualizing IoT Data at Scale With Hopara and TimescaleDB
16 May 2023, Embedded Computing Design

provided by Google News

Vitess, the database clustering system powering YouTube, graduates CNCF incubation
5 November 2019, SiliconANGLE News

PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

PlanetScale grabs YouTube-developed open-source tech, promises Vitess DBaaS with on-the-fly schema changes
18 May 2021, The Register

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

They scaled YouTube -- now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

provided by Google News



Share this page

Featured Products

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

AllegroGraph logo

Graph Database Leader for AI Knowledge Graph Applications - The Most Secure Graph Database Available.
Free Download

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Present your product here