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DBMS > Databend vs. GridGain vs. Kinetica vs. Quasardb

System Properties Comparison Databend vs. GridGain vs. Kinetica vs. Quasardb

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonGridGain  Xexclude from comparisonKinetica  Xexclude from comparisonQuasardb  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 IgniteFully vectorized database across both GPUs and CPUsDistributed, high-performance timeseries database
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.34
Rank#283  Overall
#130  Relational DBMS
Score1.55
Rank#150  Overall
#26  Key-value stores
#70  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
www.gridgain.comwww.kinetica.comquasar.ai
Technical documentationdocs.databend.comwww.gridgain.com/­docs/­index.htmldocs.kinetica.comdoc.quasar.ai/­master
DeveloperDatabend LabsGridGain Systems, Inc.Kineticaquasardb
Initial release2021200720122009
Current release1.0.59, April 2023GridGain 8.5.17.1, August 20213.14.1, January 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageRustJava, C++, .NetC, C++C++
Server operating systemshosted
Linux
macOS
Linux
OS X
Solaris
Windows
LinuxBSD
Linux
OS X
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes infointeger and binary
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 indexesnoyesyesyes infowith tags
SQL infoSupport of SQLyesANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsSQL-like query language
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
RESTful HTTP API
HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
Rust
C#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresnoyes (compute grid and cache interceptors can be used instead)user defined functionsno
Triggersnoyes (cache interceptors and events)yes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes (replicated cache)Source-replica replicationSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)nowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMyes infoTransient mode
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesSecurity Hooks for custom implementationsAccess rights for users and roles on table levelCryptographically strong user authentication and audit trail

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More resources
DatabendGridGainKineticaQuasardb
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