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DBMS > atoti vs. Kuzu vs. NSDb vs. Spark SQL vs. Yaacomo

System Properties Comparison atoti vs. Kuzu vs. NSDb vs. Spark SQL vs. Yaacomo

Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonKuzu  Xexclude from comparisonNSDb  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.An embeddable property Graph DBMS built for query speed and scalabilityScalable, High-performance Time Series DBMS designed for Real-time Analytics on top of KubernetesSpark 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 DBMSGraph DBMSTime Series DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#243  Overall
#11  Object oriented DBMS
Score0.00
Rank#402  Overall
#41  Graph DBMS
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteatoti.iokuzudb.comnsdb.iospark.apache.org/­sqlyaacomo.com
Technical documentationdocs.atoti.iodocs.kuzudb.comnsdb.io/­Architecturespark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperActiveViamApache Software FoundationQ2WEB GmbH
Initial release2022201720142009
Current release0.4.2, May 20243.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree versions availableOpen Source infoMIT licenseOpen Source infoApache Version 2.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++Java, ScalaScala
Server operating systemsserver-lessLinux
macOS
Linux
OS X
Windows
Android
Linux
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyes: int, bigint, decimal, stringyesyes
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.nononono
Secondary indexesnoall fields are automatically indexednoyes
SQL infoSupport of SQLMultidimensional Expressions (MDX)noSQL-like query languageSQL-like DML and DDL statementsyes
APIs and other access methodsCLI Client
Cypher Query Language
gRPC
HTTP REST
WebSocket
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC
C#
C++
Java
JavaScript
Python
Rust
Java
Scala
Java
Python
R
Scala
Server-side scripts infoStored proceduresPythonnonono
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningnoneShardingyes, utilizing Spark Corehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesUsing Apache Luceneyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlnonofine grained access rights according to SQL-standard

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More resources
atotiKuzuNSDbSpark SQLYaacomo
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