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DBMS > Databend vs. GridGain vs. JaguarDB

System Properties Comparison Databend vs. GridGain vs. JaguarDB

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonGridGain  Xexclude from comparisonJaguarDB  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityGridGain is an in-memory computing platform, built on Apache IgnitePerformant, highly scalable DBMS for AI and IoT applications
Primary database modelRelational DBMSKey-value store
Relational DBMS
Key-value store
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.30
Rank#287  Overall
#130  Relational DBMS
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
#13  Vector DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.gridgain.comwww.jaguardb.com
Technical documentationdocs.databend.comwww.gridgain.com/­docs/­index.htmlwww.jaguardb.com/­support.html
DeveloperDatabend LabsGridGain Systems, Inc.DataJaguar, Inc.
Initial release202120072015
Current release1.0.59, April 2023GridGain 8.5.13.3 July 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoGPL V3.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustJava, C++, .NetC++ infothe server part. Clients available in other languages
Server operating systemshosted
Linux
macOS
Linux
OS X
Solaris
Windows
Linux
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.noyesno
Secondary indexesnoyesyes
SQL infoSupport of SQLyesANSI-99 for query and DML statements, subset of DDLA subset of ANSI SQL is implemented infobut no views, foreign keys, triggers
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
C#
C++
Java
PHP
Python
Ruby
Scala
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)no
Triggersnoyes (cache interceptors and events)no
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes (replicated cache)Multi-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDno
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 controlUsers with fine-grained authorization concept, user rolesSecurity Hooks for custom implementationsrights management via user accounts

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More resources
DatabendGridGainJaguarDB
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