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DBMS > GigaSpaces vs. GridDB vs. Qdrant vs. Tarantool vs. TimescaleDB

System Properties Comparison GigaSpaces vs. GridDB vs. Qdrant vs. Tarantool vs. TimescaleDB

Editorial information provided by DB-Engines
NameGigaSpaces  Xexclude from comparisonGridDB  Xexclude from comparisonQdrant  Xexclude from comparisonTarantool  Xexclude from comparisonTimescaleDB  Xexclude from comparison
DescriptionHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsScalable in-memory time series database optimized for IoT and Big DataA high-performance vector database with neural network or semantic-based matchingIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelDocument store
Object oriented DBMS infoValues are user defined objects
Time Series DBMSVector DBMSDocument store
Key-value store
Relational DBMS
Time Series DBMS
Secondary database modelsGraph DBMS
Search engine
Key-value store
Relational DBMS
Spatial DBMS infowith Tarantool/GIS extensionRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score1.16
Rank#175  Overall
#6  Vector DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Websitewww.gigaspaces.comgriddb.netgithub.com/­qdrant/­qdrant
qdrant.tech
www.tarantool.iowww.timescale.com
Technical documentationdocs.gigaspaces.com/­latest/­landing.htmldocs.griddb.netqdrant.tech/­documentationwww.tarantool.io/­en/­docdocs.timescale.com
DeveloperGigaspaces TechnologiesToshiba CorporationQdrantVKTimescale
Initial release20002013202120082017
Current release15.5, September 20205.1, August 20222.10.0, May 20222.15.0, May 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoApache Version 2.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterpriseOpen Source infoApache 2.0
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 languageJava, C++, .NetC++RustC and C++C
Server operating systemsLinux
macOS
Solaris
Windows
LinuxDocker
Linux
macOS
Windows
BSD
Linux
macOS
Linux
OS X
Windows
Data schemeschema-freeyesschema-freeFlexible data schema: relational definition for tables with ability to store json-like documents in columnsyes
Typing infopredefined data types such as float or dateyesyes infonumerical, string, blob, geometry, boolean, timestampNumbers, Strings, Geo, Booleanstring, double, decimal, uuid, integer, blob, boolean, datetimenumerics, 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.no infoXML can be used for describing objects metadatanononoyes
Secondary indexesyesyesyes infoKeywords, numberic ranges, geo, full-textyesyes
SQL infoSupport of SQLSQL-99 for query and DML statementsSQL92, SQL-like TQL (Toshiba Query Language)noFull-featured ANSI SQL supportyes infofull PostgreSQL SQL syntax
APIs and other access methodsGigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
gRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
Open binary protocolADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
C++
Java
Python
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesnoLua, C and SQL stored proceduresuser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyes, event driven architectureyesyes, before/after data modification events, on replication events, client session eventsyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.yes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
Source-replica replicationCollection-level replicationAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
Source-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoMap-Reduce pattern can be built with XAP task executorsConnector 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 infoConsistency level configurable: ALL, QUORUM, ANYImmediate consistency within container, eventual consistency across containersEventual Consistency, tunable 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
Immediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesyesyesyes, write ahead loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesyes, full featured in-memory storage engine with persistenceno
User concepts infoAccess controlRole-based access controlAccess rights for users can be defined per databaseKey-based authenticationAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
fine grained access rights according to SQL-standard
More information provided by the system vendor
GigaSpacesGridDBQdrantTarantoolTimescaleDB
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
GigaSpacesGridDBQdrantTarantoolTimescaleDB
DB-Engines blog posts

Data processing speed and reliability: in-memory synchronous replication
9 November 2021,  Vladimir Perepelytsya, Tarantool (sponsor) 

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