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DBMS > atoti vs. Ignite vs. Spark SQL

System Properties Comparison atoti vs. Ignite vs. Spark SQL

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonIgnite  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelObject oriented DBMSKey-value store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.59
Rank#242  Overall
#10  Object oriented DBMS
Score3.64
Rank#89  Overall
#13  Key-value stores
#48  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websiteatoti.ioignite.apache.orgspark.apache.org/­sql
Technical documentationdocs.atoti.ioapacheignite.readme.io/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperActiveViamApache Software FoundationApache Software Foundation
Initial release20152014
Current releaseApache Ignite 2.63.5.0 ( 2.13), September 2023
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 languageJavaC++, Java, .NetScala
Server operating systemsLinux
OS X
Solaris
Windows
Linux
OS X
Windows
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes
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.yesno
Secondary indexesyesno
SQL infoSupport of SQLMultidimensional Expressions (MDX)ANSI-99 for query and DML statements, subset of DDLSQL-like DML and DDL statements
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
JDBC
ODBC
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresPythonyes (compute grid and cache interceptors can be used instead)no
Triggersyes (cache interceptors and events)no
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 (replicated cache)none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)
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 dataACIDno
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.yesyesno
User concepts infoAccess controlSecurity Hooks for custom implementationsno

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More resources
atotiIgniteSpark SQL
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