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DBMS > EXASOL vs. Faircom DB vs. RDF4J vs. SAP Adaptive Server vs. Spark SQL

System Properties Comparison EXASOL vs. Faircom DB vs. RDF4J vs. SAP Adaptive Server vs. Spark SQL

Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonRDF4J infoformerly known as Sesame  Xexclude from comparisonSAP Adaptive Server infoformer name: Sybase ASE  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionHigh-performance, in-memory, MPP database specifically designed for in-memory analytics.Native high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.The SAP (Sybase) Adaptive Server Enterprise (ASE) is an enterprise-class RDBMSSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value store
Relational DBMS
RDF storeRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS infowith Boeing's Spatial Query Server
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score36.31
Rank#25  Overall
#17  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.exasol.comwww.faircom.com/­products/­faircom-dbrdf4j.orgwww.sap.com/­products/­technology-platform/­sybase-ase.htmlspark.apache.org/­sql
Technical documentationwww.exasol.com/­resourcesdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlrdf4j.org/­documentationhelp.sap.com/­docs/­SAP_ASEspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperExasolFairCom CorporationSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.SAP, SybaseApache Software Foundation
Initial release20001979200419872014
Current releaseV12, November 202016.03.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availableOpen Source infoEclipse Distribution License (EDL), v1.0.commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageANSI C, C++JavaC and C++Scala
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
OS X
Unix
Windows
AIX
HP-UX
Linux
Solaris
Unix
Windows
Linux
OS X
Windows
Data schemeyesschema free, schema optional, schema required, partial schema,yes infoRDF Schemasyesyes
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyesyesyes
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 indexesyesyesyesyesno
SQL infoSupport of SQLyesyes, ANSI SQL with proprietary extensionsnoyesSQL-like DML and DDL statements
APIs and other access methods.Net
JDBC
ODBC
WebSocket
ADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
JDBC
ODBC
Supported programming languagesJava
Lua
Python
R
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Java
PHP
Python
C
C++
Cobol
Java
Java
Perl
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes info.Net, JavaScript, C/C++yesJava and Transact-SQLno
Triggersyesyesyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningnonehorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).noneMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationnonono
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 integrityyesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDtunable from ACID to Eventually ConsistentACID infoIsolation support depends on the API usedACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyes infoin-memory storage is supported as wellyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesno
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardFine grained access rights according to SQL-standard with additional protections for filesnofine grained access rights according to SQL-standardno

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More resources
EXASOLFaircom DB infoformerly c-treeACERDF4J infoformerly known as SesameSAP Adaptive Server infoformer name: Sybase ASESpark SQL
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