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DBMS > atoti vs. Heroic vs. Sequoiadb vs. Spark SQL

System Properties Comparison atoti vs. Heroic vs. Sequoiadb vs. Spark SQL

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonHeroic  Xexclude from comparisonSequoiadb  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchNewSQL database with distributed OLTP and SQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelObject oriented DBMSTime Series DBMSDocument store
Relational DBMS
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#243  Overall
#10  Object oriented DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score0.50
Rank#258  Overall
#41  Document stores
#120  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteatoti.iogithub.com/­spotify/­heroicwww.sequoiadb.comspark.apache.org/­sql
Technical documentationdocs.atoti.iospotify.github.io/­heroicwww.sequoiadb.com/­en/­index.php?m=Files&a=indexspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperActiveViamSpotifySequoiadb Ltd.Apache Software Foundation
Initial release201420132014
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree versions availableOpen Source infoApache 2.0Open Source infoServer: AGPL; Client: Apache V2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJavaC++Scala
Server operating systemsLinuxLinux
OS X
Windows
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes infooid, date, timestamp, binary, regexyes
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 indexesyes infovia Elasticsearchyesno
SQL infoSupport of SQLMultidimensional Expressions (MDX)noSQL-like query languageSQL-like DML and DDL statements
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
proprietary protocol using JSONJDBC
ODBC
Supported programming languages.Net
C++
Java
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresPythonnoJavaScriptno
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoDocument is locked during a transactionno
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.yesnonono
User concepts infoAccess controlsimple password-based access controlno

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More resources
atotiHeroicSequoiadbSpark SQL
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