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DBMS > Amazon Aurora vs. Databricks vs. Hypertable vs. TimescaleDB

System Properties Comparison Amazon Aurora vs. Databricks vs. Hypertable vs. TimescaleDB

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonDatabricks  Xexclude from comparisonHypertable  Xexclude from comparisonTimescaleDB  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonThe 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.An open source BigTable implementation based on distributed file systems such as HadoopA time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL
Primary database modelRelational DBMSDocument store
Relational DBMS
Wide column storeTime Series DBMS
Secondary database modelsDocument storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.57
Rank#51  Overall
#32  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score4.46
Rank#71  Overall
#5  Time Series DBMS
Websiteaws.amazon.com/­rds/­aurorawww.databricks.comwww.timescale.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.databricks.comdocs.timescale.com
DeveloperAmazonDatabricksHypertable Inc.Timescale
Initial release2015201320092017
Current release0.9.8.11, March 20162.15.0, May 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoGNU version 3. Commercial license availableOpen Source infoApache 2.0
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
Server operating systemshostedhostedLinux
OS X
Windows infoan inofficial Windows port is available
Linux
OS X
Windows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
Typing infopredefined data types such as float or dateyesnonumerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types
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.yesyesyes
Secondary indexesyesyesrestricted infoonly exact value or prefix value scansyes
SQL infoSupport of SQLyeswith Databricks SQLnoyes infofull PostgreSQL SQL syntax
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
C++ API
Thrift
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Python
R
Scala
C++
Java
Perl
PHP
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresyesuser defined functions and aggregatesnouser defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingyes, across time and space (hash partitioning) attributes
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesselectable replication factor on file system levelSource-replica replication with hot standby and reads on replicas info
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard
More information provided by the system vendor
Amazon AuroraDatabricksHypertableTimescaleDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Amazon AuroraDatabricksHypertableTimescaleDB
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