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DBMS > Datomic vs. Faircom DB vs. Spark SQL vs. VelocityDB

System Properties Comparison Datomic vs. Faircom DB vs. Spark SQL vs. VelocityDB

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonSpark SQL  Xexclude from comparisonVelocityDB  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Spark SQL is a component on top of 'Spark Core' for structured data processingA .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSGraph DBMS
Object oriented DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.05
Rank#358  Overall
#36  Graph DBMS
#16  Object oriented DBMS
Websitewww.datomic.comwww.faircom.com/­products/­faircom-dbspark.apache.org/­sqlvelocitydb.com
Technical documentationdocs.datomic.comdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlvelocitydb.com/­UserGuide
DeveloperCognitectFairCom CorporationApache Software FoundationVelocityDB Inc
Initial release2012197920142011
Current release1.0.6735, June 2023V12, November 20203.5.0 ( 2.13), September 20237.x
License infoCommercial or Open Sourcecommercial infolimited edition freecommercial infoRestricted, free version availableOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureANSI C, C++ScalaC#
Server operating systemsAll OS with a Java VMAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
OS X
Windows
Any that supports .NET
Data schemeyesschema free, schema optional, schema required, partial schema,yesyes
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyesyes
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.nononono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLnoyes, ANSI SQL with proprietary extensionsSQL-like DML and DDL statementsno
APIs and other access methodsRESTful HTTP APIADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBC
ODBC
.Net
Supported programming languagesClojure
Java
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Java
Python
R
Scala
.Net
Server-side scripts infoStored proceduresyes infoTransaction Functionsyes info.Net, JavaScript, C/C++nono
TriggersBy using transaction functionsyesnoCallbacks are triggered when data changes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDtunable from ACID to Eventually ConsistentnoACID
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)Yes, tunable from durable to delayed durability to in-memoryyesyes
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 developmentyesnoyes
User concepts infoAccess controlnoFine grained access rights according to SQL-standard with additional protections for filesnoBased on Windows Authentication

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More resources
DatomicFaircom DB infoformerly c-treeACESpark SQLVelocityDB
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