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 Druid vs. GridGain vs. TimescaleDB

System Properties Comparison Apache Druid vs. GridGain vs. TimescaleDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGridGain  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataGridGain is an in-memory computing platform, built on Apache IgniteA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMS
Time Series DBMS
Key-value store
Relational DBMS
Time Series DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.29
Rank#95  Overall
#49  Relational DBMS
#7  Time Series DBMS
Score1.53
Rank#155  Overall
#26  Key-value stores
#73  Relational DBMS
Score4.87
Rank#74  Overall
#4  Time Series DBMS
Websitedruid.apache.orgwww.gridgain.comwww.timescale.com
Technical documentationdruid.apache.org/­docs/­latest/­designwww.gridgain.com/­docs/­index.htmldocs.timescale.com
DeveloperApache Software Foundation and contributorsGridGain Systems, Inc.Timescale
Initial release201220072017
Current release29.0.1, April 2024GridGain 8.5.12.13.0, November 2023
License infoCommercial or Open SourceOpen Source infoApache license v2commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, C++, .NetC
Server operating systemsLinux
OS X
Unix
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyes infoschema-less columns are supportedyesyes
Typing infopredefined data types such as float or dateyesyesnumerics, 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.noyesyes
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL for queryingANSI-99 for query and DML statements, subset of DDLyes infofull PostgreSQL SQL syntax
APIs and other access methodsJDBC
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
C#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersnoyes (cache interceptors and events)yes
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesyes (replicated cache)Source-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemSecurity Hooks for custom implementationsfine grained access rights according to SQL-standard

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 DruidGridGainTimescaleDB
Recent citations in the news

'Lucifer' Botnet Turns Up the Heat on Apache Hadoop Servers
21 February 2024, Dark Reading

Apache Druid Wins Best Big Data Product in the 2023 BigDATAwire Readers' Choice Awards
26 January 2024, Datanami

New DDoS malware Attacking Apache big-data stack, Hadoop, & Druid Servers
26 February 2024, GBHackers

Imply Data gives Apache Druid schema auto-discover capability
6 June 2023, SiliconANGLE News

Imply Announces Automatic Schema Discovery for Apache Druid, Reinforcing Druid's Leadership for Real-Time ...
6 June 2023, businesswire.com

provided by Google News

GridGain's 2023 Growth Positions Company for Strong 2024
25 January 2024, Datanami

GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024
8 February 2024, PR Newswire

GridGain to Sponsor, Exhibit at Kafka Summit 2024 in London
12 March 2024, PR Newswire

GridGain Showcases Power of Apache Ignite at Community Over Code Conference
5 October 2023, Datanami

GridGain: Product Overview and Analysis
5 June 2019, eWeek

provided by Google News

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

TimescaleDB for Azure Database for PostgreSQL to power IoT and time-series workloads | Azure updates
18 March 2019, azure.microsoft.com

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

Timescale Announces Corporate Rebrand Reflecting Company's Growth
17 May 2023, PR Newswire

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

provided by Google News



Share this page

Featured Products

AllegroGraph logo

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

Ontotext logo

GraphDB allows you to link diverse data, index it for semantic search and enrich it via text analysis to build big knowledge graphs. Get it free.

Milvus logo

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

Neo4j logo

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

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

Present your product here