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DBMS > Apache Pinot vs. GridDB vs. ToroDB vs. Vertica

System Properties Comparison Apache Pinot vs. GridDB vs. ToroDB vs. Vertica

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Editorial information provided by DB-Engines
NameApache Pinot  Xexclude from comparisonGridDB  Xexclude from comparisonToroDB  Xexclude from comparisonVertica infoOpenText™ Vertica™  Xexclude from comparison
ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionRealtime distributed OLAP datastore, designed to answer OLAP queries with low latencyScalable in-memory time series database optimized for IoT and Big DataA MongoDB-compatible JSON document store, built on top of 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.
Primary database modelRelational DBMSTime Series DBMSDocument storeRelational 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
Score0.35
Rank#274  Overall
#128  Relational DBMS
Score1.91
Rank#123  Overall
#10  Time Series DBMS
Score9.62
Rank#42  Overall
#26  Relational DBMS
Websitepinot.apache.orggriddb.netgithub.com/­torodb/­serverwww.vertica.com
Technical documentationdocs.pinot.apache.orgdocs.griddb.netvertica.com/­documentation
DeveloperApache Software Foundation and contributorsToshiba Corporation8KdataOpenText infopreviously Micro Focus and Hewlett Packard
Initial release2015201320162005
Current release1.0.0, September 20235.1, August 202212.0.3, January 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen Source infoAGPL-V3commercial 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 languageJavaC++JavaC++
Server operating systemsAll OS with a Java JDK11 or higherLinuxAll OS with a Java 7 VMLinux
Data schemeyesyesschema-freeYes, 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 dateyesyes infonumerical, string, blob, geometry, boolean, timestampyes infostring, integer, double, boolean, date, object_idyes
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.nonono
Secondary indexesyesNo Indexes Required. Different internal optimization strategy, but same functionality included.
SQL infoSupport of SQLSQL-like query languageSQL92, SQL-like TQL (Toshiba Query Language)Full 1999 standard plus machine learning, time series and geospatial. Over 650 functions.
APIs and other access methodsJDBCJDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
ADO.NET
JDBC
Kafka Connector
ODBC
RESTful HTTP API
Spark Connector
vSQL infocharacter-based, interactive, front-end utility
Supported programming languagesGo
Java
Python
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Server-side scripts infoStored proceduresnoyes, PostgreSQL PL/pgSQL, with minor differences
Triggersyesnoyes, called Custom Alerts
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingShardinghorizontal partitioning, hierarchical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationMulti-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 jobsno infoBi-directional Spark integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate consistency within container, eventual consistency across containersEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID at container levelnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesno
User concepts infoAccess controlAccess rights for users can be defined per databaseAccess rights for users and rolesfine grained access rights according to SQL-standard; supports Kerberos, LDAP, Ident and hash

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More resources
Apache PinotGridDBToroDBVertica infoOpenText™ Vertica™
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