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DBMS > atoti vs. IBM Cloudant vs. Spark SQL vs. Yaacomo

System Properties Comparison atoti vs. IBM Cloudant vs. Spark SQL vs. Yaacomo

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonIBM Cloudant  Xexclude from comparisonSpark SQL  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Database as a Service offering based on Apache CouchDBSpark SQL is a component on top of 'Spark Core' for structured data processingOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelObject oriented DBMSDocument storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#243  Overall
#10  Object oriented DBMS
Score2.75
Rank#104  Overall
#19  Document stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteatoti.iowww.ibm.com/­products/­cloudantspark.apache.org/­sqlyaacomo.com
Technical documentationdocs.atoti.iocloud.ibm.com/­docs/­Cloudantspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperActiveViamIBM, Apache Software Foundation infoIBM acquired Cloudant in February 2014Apache Software FoundationQ2WEB GmbH
Initial release201020142009
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree versions availablecommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaErlangScala
Server operating systemshostedLinux
OS X
Windows
Android
Linux
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or datenoyesyes
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 indexesyesnoyes
SQL infoSupport of SQLMultidimensional Expressions (MDX)noSQL-like DML and DDL statementsyes
APIs and other access methodsRESTful HTTP/JSON APIJDBC
ODBC
JDBC
ODBC
Supported programming languagesC#
Java
JavaScript
Objective-C
PHP
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresPythonView functions (Map-Reduce) in JavaScriptno
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningShardingyes, utilizing Spark Corehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
noneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoatomic operations within a document possiblenoACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yes infoOptimistic lockingyesyes
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.yesnonoyes
User concepts infoAccess controlAccess rights for users can be defined per databasenofine grained access rights according to SQL-standard

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More resources
atotiIBM CloudantSpark SQLYaacomo
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