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DBMS > GridDB vs. SiteWhere vs. SQL.JS vs. Vertica

System Properties Comparison GridDB vs. SiteWhere vs. SQL.JS vs. Vertica

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Editorial information provided by DB-Engines
NameGridDB  Xexclude from comparisonSiteWhere  Xexclude from comparisonSQL.JS  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
DescriptionScalable in-memory time series database optimized for IoT and Big DataM2M integration platform for persisting/querying time series dataPort of SQLite to JavaScriptCloud 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.
Primary database modelTime Series DBMSTime Series DBMSRelational DBMSRelational DBMS infoColumn oriented
Secondary database modelsKey-value store
Relational DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#123  Overall
#10  Time Series DBMS
Score0.07
Rank#347  Overall
#33  Time Series DBMS
Score0.53
Rank#246  Overall
#115  Relational DBMS
Score9.62
Rank#42  Overall
#26  Relational DBMS
Websitegriddb.netgithub.com/­sitewhere/­sitewheresql.js.orgwww.vertica.com
Technical documentationdocs.griddb.netsitewhere1.sitewhere.io/­index.htmlsql.js.org/­documentation/­index.htmlvertica.com/­documentation
DeveloperToshiba CorporationSiteWhereAlon Zakai infoenhancements implemented by othersOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2013201020122005
Current release5.1, August 202212.0.3, 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 infoCommon Public Attribution License Version 1.0Open Sourcecommercial infoLimited community edition free
Cloud-based only infoOnly available as a cloud servicenononono infoon-premises, all major clouds - Amazon AWS, Microsoft Azure, Google Cloud Platform and containers
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaJavaScriptC++
Server operating systemsLinuxLinux
OS X
Windows
server-less, requires a JavaScript environment (browser, Node.js)Linux
Data schemeyespredefined schemeyesYes, but also semi-structure/unstructured data storage, and complex hierarchical data (like Parquet) stored and/or queried.
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesyesyes
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 indexesyesnoNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL92, SQL-like TQL (Toshiba Query Language)noyes infoSQL-92 is not fully supportedFull 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP RESTJavaScript APIADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesC
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
JavaScriptC#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnonoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on HBasenonehorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factor infobased on HBasenoneMulti-source replication infoOne, or more copies of data replicated across nodes, or object-store used for repository.
MapReduce infoOffers an API for user-defined Map/Reduce methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnonono infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersImmediate ConsistencynoneImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesno infoexcept by serializing a db to a fileyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyesno
User concepts infoAccess controlAccess rights for users can be defined per databaseUsers with fine-grained authorization conceptnofine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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More resources
GridDBSiteWhereSQL.JSVertica infoOpenText™ Vertica™
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