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DBMS > atoti vs. Linter vs. Splice Machine vs. SurrealDB

System Properties Comparison atoti vs. Linter vs. Splice Machine vs. SurrealDB

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonLinter  Xexclude from comparisonSplice Machine  Xexclude from comparisonSurrealDB  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.RDBMS for high security requirementsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA fully ACID transactional, developer-friendly, multi-model DBMS
Primary database modelObject oriented DBMSRelational DBMSRelational DBMSDocument store
Graph DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score0.09
Rank#346  Overall
#152  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.86
Rank#203  Overall
#34  Document stores
#18  Graph DBMS
Websiteatoti.iolinter.rusplicemachine.comsurrealdb.com
Technical documentationdocs.atoti.iosplicemachine.com/­how-it-workssurrealdb.com/­docs
DeveloperActiveViamrelex.ruSplice MachineSurrealDB Ltd
Initial release199020142022
Current release3.1, March 2021v1.1.1, January 2024
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialOpen Source infoAGPL 3.0, commercial license availableOpen Source
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 languageJavaC and C++JavaRust
Server operating systemsAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux
OS X
Solaris
Windows
Linux
macOS
Windows
Data schemeyesyesschema-free
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.no
Secondary indexesyesyes
SQL infoSupport of SQLMultidimensional Expressions (MDX)yesyesSQL-like query language
APIs and other access methodsADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
JDBC
Native Spark Datasource
ODBC
GraphQL
RESTful HTTP API
WebSocket
Supported programming languagesC
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Deno
Go
JavaScript (Node.js)
Rust
Server-side scripts infoStored proceduresPythonyes infoproprietary syntax with the possibility to convert from PL/SQLyes infoJava
Triggersyesyes
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningnoneShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyes, multi-version concurrency control (MVCC)yes
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.yesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles according to SQL-standardyes, based on authentication and database rules

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More resources
atotiLinterSplice MachineSurrealDB
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