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DBMS > Amazon Aurora vs. Brytlyt vs. Databricks vs. RethinkDB vs. RisingWave

System Properties Comparison Amazon Aurora vs. Brytlyt vs. Databricks vs. RethinkDB vs. RisingWave

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonBrytlyt  Xexclude from comparisonDatabricks  Xexclude from comparisonRethinkDB  Xexclude from comparisonRisingWave  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonScalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQLThe 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.DBMS for the Web with a mechanism to push updated query results to applications in realtime.A distributed RDBMS for stream processing, wire-compatible with PostgreSQL
Primary database modelRelational DBMSRelational DBMSDocument store
Relational DBMS
Document storeRelational DBMS
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.57
Rank#51  Overall
#32  Relational DBMS
Score0.38
Rank#276  Overall
#127  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score2.66
Rank#107  Overall
#20  Document stores
Score0.64
Rank#238  Overall
#110  Relational DBMS
Websiteaws.amazon.com/­rds/­aurorabrytlyt.iowww.databricks.comrethinkdb.comwww.risingwave.com/­database
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.brytlyt.iodocs.databricks.comrethinkdb.com/­docsdocs.risingwave.com/­docs/­current/­intro
DeveloperAmazonBrytlytDatabricksThe Linux Foundation infosince July 2017RisingWave Labs
Initial release20152016201320092022
Current release5.0, August 20232.4.1, August 20201.2, September 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2Open Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++ and CUDAC++Rust
Server operating systemshostedLinux
OS X
Windows
hostedLinux
OS X
Windows
Docker
Linux
macOS
Data schemeyesyesFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateyesyesyes infostring, binary, float, bool, date, geometryStandard SQL-types and JSON
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.yesyes infospecific XML-type available, but no XML query functionality.yesnono
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLyesyeswith Databricks SQLnoyes
APIs and other access methodsADO.NET
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
RESTful HTTP API
JDBC
PostgreSQL wire protocol
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
C
C++
Delphi
Java
Perl
Python
Tcl
Python
R
Scala
C infocommunity-supported driver
C# infocommunity-supported driver
C++ infocommunity-supported driver
Clojure infocommunity-supported driver
Dart infocommunity-supported driver
Erlang infocommunity-supported driver
Go infocommunity-supported driver
Haskell infocommunity-supported driver
Java infoofficial driver
JavaScript (Node.js) infoofficial driver
Lisp infocommunity-supported driver
Lua infocommunity-supported driver
Objective-C infocommunity-supported driver
Perl infocommunity-supported driver
PHP infocommunity-supported driver
Python infoofficial driver
Ruby infoofficial driver
Scala infocommunity-supported driver
Go
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyesuser defined functions infoin PL/pgSQLuser defined functions and aggregatesUDFs in Python or Java
TriggersyesyesClient-side triggers through changefeedsno
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding inforange based
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationyesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDAtomic single-document operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMVCC based
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardyes infousers and table-level permissionsUsers and Roles
More information provided by the system vendor
Amazon AuroraBrytlytDatabricksRethinkDBRisingWave
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
Amazon AuroraBrytlytDatabricksRethinkDBRisingWave
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