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DBMS > Amazon DocumentDB vs. Databricks vs. Kinetica vs. Quasardb

System Properties Comparison Amazon DocumentDB vs. Databricks vs. Kinetica vs. Quasardb

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonDatabricks  Xexclude from comparisonKinetica  Xexclude from comparisonQuasardb  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Fully vectorized database across both GPUs and CPUsDistributed, high-performance timeseries database
Primary database modelDocument storeDocument store
Relational DBMS
Relational DBMSTime Series DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#131  Overall
#24  Document stores
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Websiteaws.amazon.com/­documentdbwww.databricks.comwww.kinetica.comquasar.ai
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.databricks.comdocs.kinetica.comdoc.quasar.ai/­master
DeveloperDatabricksKineticaquasardb
Initial release2019201320122009
Current release7.1, August 20213.14.1, January 2024
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C++
Server operating systemshostedhostedLinuxBSD
Linux
OS X
Windows
Data schemeschema-freeFlexible Schema (defined schema, partial schema, schema free)yesschema-free
Typing infopredefined data types such as float or dateyesyesyes infointeger and binary
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.noyesnono
Secondary indexesyesyesyesyes infowith tags
SQL infoSupport of SQLnowith Databricks SQLSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresnouser defined functions and aggregatesuser defined functionsno
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesSource-replica replicationSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMyes infoTransient mode
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users and roles on table levelCryptographically strong user authentication and audit trail
More information provided by the system vendor
Amazon DocumentDBDatabricksKineticaQuasardb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Amazon DocumentDBDatabricksKineticaQuasardb
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