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DBMS > Datomic vs. RocksDB vs. SAP SQL Anywhere vs. Spark SQL

System Properties Comparison Datomic vs. RocksDB vs. SAP SQL Anywhere vs. Spark SQL

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonRocksDB  Xexclude from comparisonSAP SQL Anywhere infoformerly called Adaptive Server Anywhere  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityEmbeddable persistent key-value store optimized for fast storage (flash and RAM)RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environmentsSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.96
Rank#119  Overall
#58  Relational DBMS
Score3.58
Rank#87  Overall
#14  Key-value stores
Score5.61
Rank#64  Overall
#35  Relational DBMS
Score20.84
Rank#34  Overall
#20  Relational DBMS
Websitewww.datomic.comrocksdb.orgwww.sap.com/­products/­sql-anywhere.htmlspark.apache.org/­sql
Technical documentationdocs.datomic.comgithub.com/­facebook/­rocksdb/­wikihelp.sap.com/­sql-anywherespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperCognitectFacebook, Inc.SAP infoformerly SybaseApache Software Foundation
Initial release2012201319922014
Current release0.9.5951, July 20196.20.3, May 202117, July 20153.1.1, March 2021
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoBSDcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureC++Scala
Server operating systemsAll OS with a Java VMAIX
HP-UX
Linux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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.nonoyesno
Secondary indexesyesnoyesno
SQL infoSupport of SQLnonoyesSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIC++ API
Java API
ADO.NET
HTTP API
JDBC
ODBC
JDBC
ODBC
Supported programming languagesClojure
Java
C++
Java
C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes infoTransaction Functionsnoyes, in C/C++, Java, .Net or Perlno
TriggersBy using transaction functionsnoyesno
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersnonenoneyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersnoneSource-replica replication infoDatabase mirroringnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
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 developmentyesyesno
User concepts infoAccess controlnonofine grained access rights according to SQL-standardno

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More resources
DatomicRocksDBSAP SQL Anywhere infoformerly called Adaptive Server AnywhereSpark SQL
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