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DBMS > GridDB vs. TimescaleDB vs. Vertica vs. Warp 10

System Properties Comparison GridDB vs. TimescaleDB vs. Vertica vs. Warp 10

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonTimescaleDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparisonWarp 10  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQLCloud or off-cloud analytical database and query engine for structured and semi-structured streaming and batch data. Machine learning platform with built-in algorithms, data preparation capabilities, and model evaluation and management via SQL or Python.TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase
Primary database modelTime Series DBMSTime Series DBMSRelational DBMS infoColumn orientedTime Series DBMS
Secondary database modelsKey-value store
Relational DBMS
Relational DBMSSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.95
Rank#128  Overall
#10  Time Series DBMS
Score4.64
Rank#71  Overall
#4  Time Series DBMS
Score10.68
Rank#43  Overall
#27  Relational DBMS
Score0.07
Rank#349  Overall
#32  Time Series DBMS
Websitegriddb.netwww.timescale.comwww.vertica.comwww.warp10.io
Technical documentationdocs.griddb.netdocs.timescale.comvertica.com/­documentationwww.warp10.io/­content/­02_Getting_started
DeveloperToshiba CorporationTimescaleOpenText infopreviously Micro Focus and Hewlett PackardSenX
Initial release2013201720052015
Current release5.1, August 20222.13.0, November 202312.0.3, January 2023
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 infoLimited community edition freeOpen Source infoApache License 2.0
Cloud-based only infoOnly available as a cloud servicenonono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containersno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CC++Java
Server operating systemsLinuxLinux
OS X
Windows
LinuxLinux
OS X
Windows
Data schemeyesyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.schema-free
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampnumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data typesyesyes
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 indexesyesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.no
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)yes infofull PostgreSQL SQL syntaxFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.no
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
HTTP API
Jupyter
WebSocket
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shellyes, PostgreSQL PL/pgSQL, with minor differencesyes infoWarpScript
Triggersyesyesyes, called Custom Alertsno
Partitioning methods infoMethods for storing different data on different nodesShardingyes, across time and space (hash partitioning) attributeshorizontal partitioning, hierarchical partitioningSharding infobased on HBase
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replication with hot standby and reads on replicas infoMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.selectable replication factor infobased on HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnono infoBi-directional Spark integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencyImmediate ConsistencyImmediate Consistency infobased on HBase
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelACIDACIDno
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.yesnonoyes
User concepts infoAccess controlAccess rights for users can be defined per databasefine grained access rights according to SQL-standardfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hashMandatory use of cryptographic tokens, containing fine-grained authorizations
More information provided by the system vendor
GridDBTimescaleDBVertica infoOpenText™ Vertica™Warp 10
Specific characteristicsGridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Deploy-anywhere database for large-scale analytical deployments. Deploy off-cloud,...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Fast, scalable, and capable of high concurrency. Separation of compute/storage leverages...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Communication and network analytics, Embedded analytics, Fraud monitoring and Risk...
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Abiba Systems, Adform, adMarketplace, AmeriPride, Anritsu, AOL, Avito, Auckland Transport,...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more
Cost-based models and subscription-based models are both available. One license is...
» more

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GridDBTimescaleDBVertica infoOpenText™ Vertica™Warp 10
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