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DBMS > atoti vs. Spark SQL vs. SwayDB

System Properties Comparison atoti vs. Spark SQL vs. SwayDB

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonSpark SQL  Xexclude from comparisonSwayDB  Xexclude from comparison
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 processingAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelObject oriented DBMSRelational DBMSKey-value store
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
Score0.00
Rank#382  Overall
#59  Key-value stores
Websiteatoti.iospark.apache.org/­sqlswaydb.simer.au
Technical documentationdocs.atoti.iospark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperActiveViamApache Software FoundationSimer Plaha
Initial release20142018
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree versions availableOpen Source infoApache 2.0Open Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaScalaScala
Server operating systemsLinux
OS X
Windows
Data schemeyesschema-free
Typing infopredefined data types such as float or dateyesno
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.nono
Secondary indexesnono
SQL infoSupport of SQLMultidimensional Expressions (MDX)SQL-like DML and DDL statementsno
APIs and other access methodsJDBC
ODBC
Supported programming languagesJava
Python
R
Scala
Java
Kotlin
Scala
Server-side scripts infoStored proceduresPythonnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlnono

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atotiSpark SQLSwayDB
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