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DBMS > EXASOL vs. Faircom DB vs. IRONdb vs. Memcached vs. Spark SQL

System Properties Comparison EXASOL vs. Faircom DB vs. IRONdb vs. Memcached vs. Spark SQL

Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonIRONdb  Xexclude from comparisonMemcached  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 Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityIn-memory key-value store, originally intended for cachingSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSKey-value store
Relational DBMS
Time Series DBMSKey-value 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
Score19.42
Rank#32  Overall
#4  Key-value stores
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.exasol.comwww.faircom.com/­products/­faircom-dbwww.circonus.com/solutions/time-series-database/www.memcached.orgspark.apache.org/­sql
Technical documentationwww.exasol.com/­resourcesdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.circonus.com/irondb/category/getting-startedgithub.com/­memcached/­memcached/­wikispark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperExasolFairCom CorporationCirconus LLC.Danga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalApache Software Foundation
Initial release20001979201720032014
Current releaseV12, November 2020V0.10.20, January 20181.6.25, March 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial infoRestricted, free version availablecommercialOpen Source infoBSD licenseOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++C and C++CScala
Server operating systemsAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
LinuxFreeBSD
Linux
OS X
Unix
Windows
Linux
OS X
Windows
Data schemeyesschema free, schema optional, schema required, partial schema,schema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyes infotext, numeric, histogramsnoyes
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 indexesyesyesnonono
SQL infoSupport of SQLyesyes, ANSI SQL with proprietary extensionsSQL-like query language (Circonus Analytics Query Language: CAQL)noSQL-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
HTTP APIProprietary protocolJDBC
ODBC
Supported programming languagesJava
Lua
Python
R
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes info.Net, JavaScript, C/C++yes, in Luanono
Triggersyesyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningAutomatic, metric affinity per nodenoneyes, 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 infoRepcached, a Memcached patch, provides this functionallitynone
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 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-memoryyesnoyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnono
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 filesnoyes infousing SASL (Simple Authentication and Security Layer) protocolno

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More resources
EXASOLFaircom DB infoformerly c-treeACEIRONdbMemcachedSpark SQL
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