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DBMS > Apache Impala vs. SiriDB vs. Spark SQL vs. Transbase

System Properties Comparison Apache Impala vs. SiriDB vs. Spark SQL vs. Transbase

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonSiriDB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopOpen Source Time Series DBMSSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websiteimpala.apache.orgsiridb.comspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationimpala.apache.org/­impala-docs.htmldocs.siridb.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCesbitApache Software FoundationTransaction Software GmbH
Initial release2013201720141987
Current release4.1.0, June 20223.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoMIT LicenseOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CScalaC and C++
Server operating systemsLinuxLinuxLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyes infoNumeric datayesyes
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 indexesyesyesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
HTTP APIJDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesAll languages supporting JDBC/ODBCC
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoyes
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoyes
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.noyesnono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberossimple rights management via user accountsnofine grained access rights according to SQL-standard

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More resources
Apache ImpalaSiriDBSpark SQLTransbase
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