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DBMS > atoti vs. Datomic vs. Qdrant vs. Spark SQL

System Properties Comparison atoti vs. Datomic vs. Qdrant vs. Spark SQL

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Editorial information provided by DB-Engines
Nameatoti  Xexclude from comparisonDatomic  Xexclude from comparisonQdrant  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionAn in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityA high-performance vector database with neural network or semantic-based matchingSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelObject oriented DBMSRelational DBMSVector DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.61
Rank#243  Overall
#10  Object oriented DBMS
Score1.66
Rank#144  Overall
#66  Relational DBMS
Score1.28
Rank#167  Overall
#6  Vector DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteatoti.iowww.datomic.comgithub.com/­qdrant/­qdrant
qdrant.tech
spark.apache.org/­sql
Technical documentationdocs.atoti.iodocs.datomic.comqdrant.tech/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperActiveViamCognitectQdrantApache Software Foundation
Initial release201220212014
Current release1.0.7075, December 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree versions availablecommercial infolimited edition freeOpen Source infoApache Version 2.0Open 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 languageJavaJava, ClojureRustScala
Server operating systemsAll OS with a Java VMDocker
Linux
macOS
Windows
Linux
OS X
Windows
Data schemeyesschema-freeyes
Typing infopredefined data types such as float or dateyesNumbers, Strings, Geo, Booleanyes
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 indexesyesyes infoKeywords, numberic ranges, geo, full-textno
SQL infoSupport of SQLMultidimensional Expressions (MDX)nonoSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIgRPC
OpenAPI 3.0
RESTful HTTP/JSON API infoOpenAPI 3.0
JDBC
ODBC
Supported programming languagesClojure
Java
.Net
Go
Java
JavaScript (Node.js)
Python
Rust
Java
Python
R
Scala
Server-side scripts infoStored proceduresPythonyes infoTransaction Functionsno
TriggersBy using transaction functionsno
Partitioning methods infoMethods for storing different data on different nodesSharding, horizontal partitioningnone infoBut extensive use of caching in the application peersShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersCollection-level replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency, tunable 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)yesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes inforecommended only for testing and developmentyesno
User concepts infoAccess controlnoKey-based authenticationno

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atotiDatomicQdrantSpark SQL
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