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DBMS > atoti vs. Spark SQL vs. Transbase vs. Yanza

System Properties Comparison atoti vs. Spark SQL vs. Transbase vs. Yanza

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Spark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMSTime Series DBMS for IoT Applications
Primary database modelObject oriented DBMSRelational DBMSRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.56
Rank#245  Overall
#10  Object oriented DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websiteatoti.iospark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.htmlyanza.com
Technical documentationdocs.atoti.iospark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperActiveViamApache Software FoundationTransaction Software GmbHYanza
Initial release201419872015
Current release3.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open Sourcecommercial infofree versions availableOpen Source infoApache 2.0commercial infofree development licensecommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenononono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScalaC and C++
Server operating systemsLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Windows
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesno
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 indexesnoyesno
SQL infoSupport of SQLMultidimensional Expressions (MDX)SQL-like DML and DDL statementsyesno
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
HTTP API
Supported programming languagesJava
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
any language that supports HTTP calls
Server-side scripts infoStored proceduresPythonnoyesno
Triggersnoyesyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesno
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlnofine grained access rights according to SQL-standardno

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More resources
atotiSpark SQLTransbaseYanza
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