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

DBMS > GridDB vs. GridGain vs. Pinecone vs. ToroDB

System Properties Comparison GridDB vs. GridGain vs. Pinecone vs. ToroDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonGridGain  Xexclude from comparisonPinecone  Xexclude from comparisonToroDB  Xexclude from comparison
ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionScalable in-memory time series database optimized for IoT and Big DataGridGain is an in-memory computing platform, built on Apache IgniteA managed, cloud-native vector databaseA MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelTime Series DBMSKey-value store
Relational DBMS
Vector DBMSDocument store
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
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score3.16
Rank#95  Overall
#2  Vector DBMS
Websitegriddb.netwww.gridgain.comwww.pinecone.iogithub.com/­torodb/­server
Technical documentationdocs.griddb.netwww.gridgain.com/­docs/­index.htmldocs.pinecone.io/­docs/­overview
DeveloperToshiba CorporationGridGain Systems, Inc.Pinecone Systems, Inc8Kdata
Initial release2013200720192016
Current release5.1, August 2022GridGain 8.5.1
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialcommercialOpen Source infoAGPL-V3
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java, C++, .NetJava
Server operating systemsLinuxLinux
OS X
Solaris
Windows
hostedAll OS with a Java 7 VM
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesString, Number, Booleanyes infostring, integer, double, boolean, date, object_id
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.noyesnono
Secondary indexesyesyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)ANSI-99 for query and DML statements, subset of DDLno
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
RESTful HTTP API
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
Python
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)
Triggersyesyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes (replicated cache)Source-replica replication
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 ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelACIDno
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.yesyesno
User concepts infoAccess controlAccess rights for users can be defined per databaseSecurity Hooks for custom implementationsAccess rights for users and roles
More information provided by the system vendor
GridDBGridGainPineconeToroDB
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
GridDBGridGainPineconeToroDB
DB-Engines blog posts

Vector databases
2 June 2023, Matthias Gelbmann

show all

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

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

Leveraging Open Source Tools for IoT - open source for you
19 February 2020, Open Source For You

provided by Google News

GridGain in-memory data and generative AI – Blocks and Files
10 May 2024, Blocks & Files

GridGain to Sponsor and Speak at Three Key Industry Events in May 2024
2 May 2024, PR Newswire

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

GridGain Named in the 2023 Gartner® Market Guide for Event Stream Processing
22 August 2023, GlobeNewswire

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

provided by Google News

Pinecone’s new serverless database may see few takers, analysts say
17 January 2024, InfoWorld

Pinecone Unveils Serverless Vector Database for Enhanced AI Applications
16 January 2024, Datanami

Pinecone Brings Serverless To Vector Databases
16 January 2024, Forbes

Pinecone: New vector database architecture a 'breakthrough' to curb AI hallucinations
16 January 2024, VentureBeat

Reimagining Vector Databases for the Generative AI Era with Pinecone Serverless on AWS | Amazon Web Services
21 March 2024, AWS Blog

provided by Google News



Share this page

Featured Products

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

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.

AllegroGraph logo

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

RaimaDB logo

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

Present your product here