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DBMS > atoti vs. Prometheus vs. Spark SQL

System Properties Comparison atoti vs. Prometheus vs. Spark SQL

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonPrometheus  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Open-source TimeSeries DBMS and monitoring systemSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelObject oriented DBMSTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.36
Rank#263  Overall
#15  Object oriented DBMS
Score6.32
Rank#67  Overall
#3  Time Series DBMS
Score23.12
Rank#35  Overall
#21  Relational DBMS
Websitewww.atoti.ioprometheus.iospark.apache.org/­sql
Technical documentationprometheus.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperActiveViamApache Software Foundation
Initial release20152014
Current release3.2.0, October 2021
License infoCommercial or Open Sourcecommercial infofree versions availableOpen Source infoApache 2.0Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaGoScala
Server operating systemsLinux
Windows
Linux
OS X
Windows
Data schemeyesyes
Typing infopredefined data types such as float or dateNumeric data onlyyes
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.no infoImport of XML data possibleno
Secondary indexesnono
SQL infoSupport of SQLMultidimensional Expressions (MDX)noSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP/JSON APIJDBC
ODBC
Supported programming languages.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresPythonnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoby Federationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemnone
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
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.yesnono
User concepts infoAccess controlnono

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atotiPrometheusSpark SQL
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