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DBMS > GridGain vs. PostgreSQL vs. QuestDB vs. Spark SQL

System Properties Comparison GridGain vs. PostgreSQL vs. QuestDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonPostgreSQL  Xexclude from comparisonQuestDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLA high performance open source SQL database for time series dataSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelKey-value store
Relational DBMS
Relational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Time Series DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Score2.52
Rank#109  Overall
#9  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.gridgain.comwww.postgresql.orgquestdb.iospark.apache.org/­sql
Technical documentationwww.gridgain.com/­docs/­index.htmlwww.postgresql.org/­docsquestdb.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGridGain Systems, Inc.PostgreSQL Global Development Group infowww.postgresql.org/­developerQuestDB Technology IncApache Software Foundation
Initial release20071989 info1989: Postgres, 1996: PostgreSQL20142014
Current releaseGridGain 8.5.116.3, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSDOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetCJava (Zero-GC), C++, RustScala
Server operating systemsLinux
OS X
Solaris
Windows
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeyesyesyes infoschema-free via InfluxDB Line Protocolyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.yesyes infospecific XML-type available, but no XML query functionality.nono
Secondary indexesyesyesnono
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLyes infostandard with numerous extensionsSQL with time-series extensionsSQL-like DML and DDL statements
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
JDBC
ODBC
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)user defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.nono
Triggersyes (cache interceptors and events)yesnono
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and (since PostgreSQL 11) by hashhorizontal partitioning (by timestamps)yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)Source-replica replication infoother methods possible by using 3rd party extensionsSource-replica replication with eventual consistencynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID for single-table writesno
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.yesnoyes infothrough memory mapped filesno
User concepts infoAccess controlSecurity Hooks for custom implementationsfine grained access rights according to SQL-standardno
More information provided by the system vendor
GridGainPostgreSQLQuestDBSpark SQL
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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