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DBMS > Amazon Redshift vs. Databricks vs. PostgreSQL vs. VoltDB

System Properties Comparison Amazon Redshift vs. Databricks vs. PostgreSQL vs. VoltDB

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Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonDatabricks  Xexclude from comparisonPostgreSQL  Xexclude from comparisonVoltDB  Xexclude from comparison
DescriptionLarge scale data warehouse service for use with business intelligence toolsThe 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.Widely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLDistributed In-Memory NewSQL RDBMS infoUsed for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory
Primary database modelRelational DBMSDocument store
Relational DBMS
Relational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Relational DBMS
Secondary database modelsDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score16.88
Rank#35  Overall
#22  Relational DBMS
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score636.25
Rank#4  Overall
#4  Relational DBMS
Score1.47
Rank#157  Overall
#73  Relational DBMS
Websiteaws.amazon.com/­redshiftwww.databricks.comwww.postgresql.orgwww.voltdb.com
Technical documentationdocs.aws.amazon.com/­redshiftdocs.databricks.comwww.postgresql.org/­docsdocs.voltdb.com
DeveloperAmazon (based on PostgreSQL)DatabricksPostgreSQL Global Development Group infowww.postgresql.org/­developerVoltDB Inc.
Initial release201220131989 info1989: Postgres, 1996: PostgreSQL2010
Current release16.3, May 202411.3, April 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSDOpen Source infoAGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCCJava, C++
Server operating systemshostedhostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
OS X infofor development
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyesyes
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.noyesyes infospecific XML-type available, but no XML query functionality.
Secondary indexesrestrictedyesyesyes
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardwith Databricks SQLyes infostandard with numerous extensionsyes infoonly a subset of SQL 99
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Java API
JDBC
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C#
C++
Erlang infonot officially supported
Go
Java
JavaScript infoNode.js
PHP
Python
Server-side scripts infoStored proceduresuser defined functions infoin Pythonuser defined functions and aggregatesuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.Java
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingpartitioning by range, list and (since PostgreSQL 11) by hashSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesSource-replica replication infoother methods possible by using 3rd party extensionsMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemyesno infoFOREIGN KEY constraints are not supported
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID infoTransactions are executed single-threaded within stored procedures
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoData access is serialized by the server
Durability infoSupport for making data persistentyesyesyesyes infoSnapshots and command logging
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-standardfine grained access rights according to SQL-standardUsers and roles with access to stored procedures
More information provided by the system vendor
Amazon RedshiftDatabricksPostgreSQLVoltDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
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