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DBMS > EXASOL vs. IRONdb vs. Spark SQL vs. SQream DB

System Properties Comparison EXASOL vs. IRONdb vs. Spark SQL vs. SQream DB

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Editorial information provided by DB-Engines
NameEXASOL  Xexclude from comparisonIRONdb  Xexclude from comparisonSpark SQL  Xexclude from comparisonSQream DB  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.A 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 processinga GPU-based, columnar RDBMS for big data analytics workloads
Primary database modelRelational DBMSTime Series DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.99
Rank#124  Overall
#58  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.70
Rank#227  Overall
#104  Relational DBMS
Websitewww.exasol.comwww.circonus.com/solutions/time-series-database/spark.apache.org/­sqlsqream.com
Technical documentationwww.exasol.com/­resourcesdocs.circonus.com/irondb/category/getting-startedspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.sqream.com
DeveloperExasolCirconus LLC.Apache Software FoundationSQream Technologies
Initial release2000201720142017
Current releaseV0.10.20, January 20183.5.0 ( 2.13), September 20232022.1.6, December 2022
License infoCommercial or Open SourcecommercialcommercialOpen 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 languageC and C++ScalaC++, CUDA, Haskell, Java, Scala
Server operating systemsLinuxLinux
OS X
Windows
Linux
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyesyes, ANSI Standard SQL Types
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 indexesyesnonono
SQL infoSupport of SQLyesSQL-like query language (Circonus Analytics Query Language: CAQL)SQL-like DML and DDL statementsyes
APIs and other access methods.Net
JDBC
ODBC
WebSocket
HTTP APIJDBC
ODBC
.Net
JDBC
ODBC
Supported programming languagesJava
Lua
Python
R
.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
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresuser defined functionsyes, in Luanouser defined functions in Python
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesShardingAutomatic, metric affinity per nodeyes, utilizing Spark Corehorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter awarenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoHadoop integrationnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency per node, eventual consistency across nodesImmediate Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardnono

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More resources
EXASOLIRONdbSpark SQLSQream DB
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