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DBMS > EXASOL vs. Faircom DB vs. Microsoft Access vs. RDF4J vs. Spark SQL

System Properties Comparison EXASOL vs. Faircom DB vs. Microsoft Access vs. RDF4J vs. Spark SQL

Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonRDF4J infoformerly known as Sesame  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.Microsoft 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.)RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value store
Relational DBMS
Relational DBMSRDF storeRelational DBMS
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
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score0.69
Rank#230  Overall
#9  RDF stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.exasol.comwww.faircom.com/­products/­faircom-dbwww.microsoft.com/­en-us/­microsoft-365/­accessrdf4j.orgspark.apache.org/­sql
Technical documentationwww.exasol.com/­resourcesdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldeveloper.microsoft.com/­en-us/­accessrdf4j.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperExasolFairCom CorporationMicrosoftSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Apache Software Foundation
Initial release20001979199220042014
Current releaseV12, November 20201902 (16.0.11328.20222), March 20193.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availablecommercial infoBundled with Microsoft OfficeOpen Source infoEclipse Distribution License (EDL), v1.0.Open 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++C++JavaScala
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Windows infoNot a real database server, but making use of DLLsLinux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeyesschema free, schema optional, schema required, partial schema,yesyes infoRDF Schemasyes
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.nonono
Secondary indexesyesyesyesyesno
SQL infoSupport of SQLyesyes, ANSI SQL with proprietary extensionsyes infobut not compliant to any SQL standardnoSQL-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
ADO.NET
DAO
ODBC
OLE DB
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
JDBC
ODBC
Supported programming languagesJava
Lua
Python
R
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes info.Net, JavaScript, C/C++yes infosince Access 2010 using the ACE-engineyesno
Triggersyesyesyes infosince Access 2010 using the ACE-engineyesno
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningnonenoneyes, 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).nonenonenone
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
Foreign keys infoReferential integrityyesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDtunable from ACID to Eventually ConsistentACID infobut no files for transaction loggingACID infoIsolation support depends on the API usedno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyes infobut no files for transaction loggingyes infoin-memory storage is supported as wellyes
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 filesno infoa simple user-level security was built in till version Access 2003nono

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More resources
EXASOLFaircom DB infoformerly c-treeACEMicrosoft AccessRDF4J infoformerly known as SesameSpark SQL
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