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DBMS > GridDB vs. Pinecone vs. SiteWhere vs. Tarantool

System Properties Comparison GridDB vs. Pinecone vs. SiteWhere vs. Tarantool

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonPinecone  Xexclude from comparisonSiteWhere  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataA managed, cloud-native vector databaseM2M integration platform for persisting/querying time series dataIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelTime Series DBMSVector DBMSTime Series DBMSDocument store
Key-value store
Relational DBMS
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score3.23
Rank#92  Overall
#3  Vector DBMS
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Score1.67
Rank#143  Overall
#25  Document stores
#25  Key-value stores
#65  Relational DBMS
Websitegriddb.netwww.pinecone.iogithub.com/­sitewhere/­sitewherewww.tarantool.io
Technical documentationdocs.griddb.netdocs.pinecone.io/­docs/­overviewsitewhere1.sitewhere.io/­index.htmlwww.tarantool.io/­en/­doc
DeveloperToshiba CorporationPinecone Systems, IncSiteWhereVK
Initial release2013201920102008
Current release5.1, August 20222.10.0, May 2022
License infoCommercial or Open SourceOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availablecommercialOpen Source infoCommon Public Attribution License Version 1.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC and C++
Server operating systemsLinuxhostedLinux
OS X
Windows
BSD
Linux
macOS
Data schemeyespredefined schemeFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampString, Number, Booleanyesstring, double, decimal, uuid, integer, blob, boolean, datetime
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.nononono
Secondary indexesyesnoyes
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)nonoFull-featured ANSI SQL support
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
RESTful HTTP APIHTTP RESTOpen binary protocol
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
PythonC
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresnoLua, C and SQL stored procedures
Triggersyesyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on HBaseSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factor infobased on HBaseAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyCasual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlAccess rights for users can be defined per databaseUsers with fine-grained authorization conceptAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
More information provided by the system vendor
GridDBPineconeSiteWhereTarantool
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

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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
GridDBPineconeSiteWhereTarantool
DB-Engines blog posts

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2 June 2023, Matthias Gelbmann

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9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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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

General Availability of GridDB 5.3 Enterprise Edition ~ Major Enhancement in IoT and Time Series Data Analysis ...
16 May 2023, global.toshiba

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

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

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

provided by Google News

PostgreSQL is Now Faster than Pinecone, 75% Cheaper, with New Open Source Extensions
11 June 2024, PR Newswire

Pinecone launches its serverless vector database out of preview
14 June 2024, Yahoo Movies UK

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

Pinecone launches its serverless vector database out of preview
21 May 2024, TechCrunch

A New Era AI Databases: PostgreSQL with pgvectorscale Outperforms Pinecone and Cuts Costs by 75% with New Open-Source Extensions
12 June 2024, MarkTechPost

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SiteWhere: An open platform for connected devices
11 July 2017, Open Source For You

11 Best Open source IoT Platforms To Develop Smart Projects
9 March 2023, H2S Media

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Tarantool Announces New Enterprise Version With Enhanced Scaling and Monitoring Capabilities
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