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DBMS > EXASOL vs. Faircom DB vs. Graph Engine vs. IRONdb vs. Spark SQL

System Properties Comparison EXASOL vs. Faircom DB vs. Graph Engine vs. IRONdb vs. Spark SQL

Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonIRONdb  Xexclude from comparisonSpark SQL  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
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.A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineA distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicitySpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value store
Relational DBMS
Graph DBMS
Key-value store
Time Series DBMSRelational 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
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.exasol.comwww.faircom.com/­products/­faircom-dbwww.graphengine.iowww.circonus.com/solutions/time-series-database/spark.apache.org/­sql
Technical documentationwww.exasol.com/­resourcesdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlwww.graphengine.io/­docs/­manualdocs.circonus.com/irondb/category/getting-startedspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperExasolFairCom CorporationMicrosoftCirconus LLC.Apache Software Foundation
Initial release20001979201020172014
Current releaseV12, November 2020V0.10.20, January 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availableOpen Source infoMIT LicensecommercialOpen 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++.NET and CC and C++Scala
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
.NETLinuxLinux
OS X
Windows
Data schemeyesschema free, schema optional, schema required, partial schema,yesschema-freeyes
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyesyes infotext, numeric, histogramsyes
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.nonononono
Secondary indexesyesyesnono
SQL infoSupport of SQLyesyes, ANSI SQL with proprietary extensionsnoSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-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
RESTful HTTP APIHTTP APIJDBC
ODBC
Supported programming languagesJava
Lua
Python
R
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C#
C++
F#
Visual Basic
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes info.Net, JavaScript, C/C++yesyes, in Luano
Triggersyesyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioninghorizontal partitioningAutomatic, metric affinity per nodeyes, 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).configurable replication factor, datacenter awarenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate consistency per node, eventual consistency across nodes
Foreign keys infoReferential integrityyesyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDtunable from ACID to Eventually Consistentnonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesnono
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 filesnono

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More resources
EXASOLFaircom DB infoformerly c-treeACEGraph Engine infoformer name: TrinityIRONdbSpark SQL
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