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DBMS > atoti vs. GridGain vs. Kinetica vs. SQLite vs. Stardog

System Properties Comparison atoti vs. GridGain vs. Kinetica vs. SQLite vs. Stardog

Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonGridGain  Xexclude from comparisonKinetica  Xexclude from comparisonSQLite  Xexclude from comparisonStardog  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.GridGain is an in-memory computing platform, built on Apache IgniteFully vectorized database across both GPUs and CPUsWidely used embeddable, in-process RDBMSEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization
Primary database modelObject oriented DBMSKey-value store
Relational DBMS
Relational DBMSRelational DBMSGraph DBMS
RDF store
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.56
Rank#249  Overall
#10  Object oriented DBMS
Score1.59
Rank#158  Overall
#26  Key-value stores
#73  Relational DBMS
Score0.74
Rank#229  Overall
#105  Relational DBMS
Score118.16
Rank#10  Overall
#7  Relational DBMS
Score2.03
Rank#136  Overall
#12  Graph DBMS
#6  RDF stores
Websiteatoti.iowww.gridgain.comwww.kinetica.comwww.sqlite.orgwww.stardog.com
Technical documentationdocs.atoti.iowww.gridgain.com/­docs/­index.htmldocs.kinetica.comwww.sqlite.org/­docs.htmldocs.stardog.com
DeveloperActiveViamGridGain Systems, Inc.KineticaDwayne Richard HippStardog-Union
Initial release2007201220002010
Current releaseGridGain 8.5.17.1, August 20213.45.2  (12 March 2024), March 20247.3.0, May 2020
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialcommercialOpen Source infoPublic Domaincommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava, C++, .NetC, C++CJava
Server operating systemsLinux
OS X
Solaris
Windows
Linuxserver-lessLinux
macOS
Windows
Data schemeyesyesyes infodynamic column typesschema-free and OWL/RDFS-schema support
Typing infopredefined data types such as float or dateyesyesyes infonot rigid because of 'dynamic typing' concept.yes
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.yesnonono infoImport/export of XML data possible
Secondary indexesyesyesyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLMultidimensional Expressions (MDX)ANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statementsyes infoSQL-92 is not fully supportedYes, compatible with all major SQL variants through dedicated BI/SQL Server
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
RESTful HTTP API
ADO.NET infoinofficial driver
JDBC infoinofficial driver
ODBC infoinofficial driver
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
C++
Java
JavaScript (Node.js)
Python
Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
Server-side scripts infoStored proceduresPythonyes (compute grid and cache interceptors can be used instead)user defined functionsnouser defined functions and aggregates, HTTP Server extensions in Java
Triggersyes (cache interceptors and events)yes infotriggers when inserted values for one or more columns fall within a specified rangeyesyes infovia event handlers
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes (replicated cache)Source-replica replicationnoneMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)nonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency in HA-Cluster
Foreign keys infoReferential integritynoyesyesyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes infovia file-system locksyes
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.yesyesyes infoGPU vRAM or System RAMyesyes
User concepts infoAccess controlSecurity Hooks for custom implementationsAccess rights for users and roles on table levelnoAccess rights for users and roles

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More resources
atotiGridGainKineticaSQLiteStardog
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