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DBMS > Datomic vs. LevelDB vs. Microsoft Access vs. Splice Machine vs. ToroDB

System Properties Comparison Datomic vs. LevelDB vs. Microsoft Access vs. Splice Machine vs. ToroDB

Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonLevelDB  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSplice Machine  Xexclude from comparisonToroDB  Xexclude from comparison
ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityEmbeddable fast key-value storage library that provides an ordered mapping from string keys to string valuesMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkA MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelRelational DBMSKey-value storeRelational DBMSRelational DBMSDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score2.35
Rank#111  Overall
#19  Key-value stores
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.datomic.comgithub.com/­google/­leveldbwww.microsoft.com/­en-us/­microsoft-365/­accesssplicemachine.comgithub.com/­torodb/­server
Technical documentationdocs.datomic.comgithub.com/­google/­leveldb/­blob/­main/­doc/­index.mddeveloper.microsoft.com/­en-us/­accesssplicemachine.com/­how-it-works
DeveloperCognitectGoogleMicrosoftSplice Machine8Kdata
Initial release20122011199220142016
Current release1.0.6735, June 20231.23, February 20211902 (16.0.11328.20222), March 20193.1, March 2021
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoBSDcommercial infoBundled with Microsoft OfficeOpen Source infoAGPL 3.0, commercial license availableOpen Source infoAGPL-V3
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++C++JavaJava
Server operating systemsAll OS with a Java VMIllumos
Linux
OS X
Windows
Windows infoNot a real database server, but making use of DLLsLinux
OS X
Solaris
Windows
All OS with a Java 7 VM
Data schemeyesschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesnoyesyesyes infostring, integer, double, boolean, date, object_id
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.nonono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLnonoyes infobut not compliant to any SQL standardyes
APIs and other access methodsRESTful HTTP APIADO.NET
DAO
ODBC
OLE DB
JDBC
Native Spark Datasource
ODBC
Supported programming languagesClojure
Java
C++
Go
Java info3rd party binding
JavaScript (Node.js) info3rd party binding
Python info3rd party binding
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsnoyes infosince Access 2010 using the ACE-engineyes infoJava
TriggersBy using transaction functionsnoyes infosince Access 2010 using the ACE-engineyesno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersnonenoneShared Nothhing Auto-Sharding, Columnar PartitioningSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersnonenoneMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infobut no files for transaction loggingACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes infowith automatic compression on writesyes infobut no files for transaction loggingyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentyes
User concepts infoAccess controlnonono infoa simple user-level security was built in till version Access 2003Access rights for users, groups and roles according to SQL-standardAccess rights for users and roles

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More resources
DatomicLevelDBMicrosoft AccessSplice MachineToroDB
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