DB-EnginesExtremeDB for everyone with an RTOSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > GridDB vs. Ignite vs. Microsoft Azure Synapse Analytics

System Properties Comparison GridDB vs. Ignite vs. Microsoft Azure Synapse Analytics

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonIgnite  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server
Primary database modelTime Series DBMSKey-value store
Relational DBMS
Relational DBMS
Secondary database modelsKey-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score3.16
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score20.56
Rank#31  Overall
#19  Relational DBMS
Websitegriddb.netignite.apache.orgazure.microsoft.com/­services/­synapse-analytics
Technical documentationdocs.griddb.netapacheignite.readme.io/­docsdocs.microsoft.com/­azure/­synapse-analytics
DeveloperToshiba CorporationApache Software FoundationMicrosoft
Initial release201320152016
Current release5.1, August 2022Apache Ignite 2.6
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++C++, Java, .NetC++
Server operating systemsLinuxLinux
OS X
Solaris
Windows
hosted
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesyes
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.noyesno
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)ANSI-99 for query and DML statements, subset of DDLyes
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
ODBC
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
C#
Java
PHP
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)Transact SQL
Triggersyesyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding, horizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes (replicated cache)yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraints
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelACIDACID
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.yesyes
User concepts infoAccess controlAccess rights for users can be defined per databaseSecurity Hooks for custom implementationsyes
More information provided by the system vendor
GridDBIgniteMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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
GridDBIgniteMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse
Recent citations in the news

General Availability of GridDB® 5.5 Enterprise Edition ~Enhancing the efficiency of IoT system development and ...
16 January 2024, global.toshiba

Toshiba launches cloudy managed IoT database service running its own GridDB
8 April 2021, The Register

GridDB Use case Large-scale high-speed processing of smart meter data following the deregulation of electrical power ...
1 November 2020, global.toshiba

General Availability of GridDB 5.1 Enterprise Edition ~ Continuous database usage in the event of data center failure ...
19 August 2022, global.toshiba

Toshiba's Distributed Database GridDB(R) Now Features Scale-Out and Scale-Up combo for Petabyte-scale Data ...
3 December 2019, global.toshiba

provided by Google News

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

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

Apache Ignite: An Overview
6 September 2023, Open Source For You

What is Apache Ignite? How is Apache Ignite Used?
18 July 2022, The Stack

ArcGIS and Apache Log4j Vulnerabilities
22 May 2023, Esri

provided by Google News

General Available: Azure Synapse Runtime for Apache Spark 3.4 is now GA | Azure updates
8 April 2024, Microsoft

Migrate Microsoft Azure Synapse Analytics to Amazon Redshift using AWS SCT | Amazon Web Services
18 October 2023, AWS Blog

Azure Synapse vs. Databricks: Data Platform Comparison 2024
26 March 2024, eWeek

Azure Synapse Runtime for Apache Spark 3.2 End of Support | Azure updates
22 March 2024, Microsoft

Azure Synapse Analytics: Everything you need to know about Microsoft's cloud analytics platform
24 September 2023, DataScientest

provided by Google News



Share this page

Featured Products

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

RaimaDB logo

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

SingleStore logo

Build AI apps with Vectors on SQL and JSON with milliseconds response times.
Try it today.

Present your product here