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DBMS > Databricks vs. Postgres-XL vs. Teradata

System Properties Comparison Databricks vs. Postgres-XL vs. Teradata

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonPostgres-XL  Xexclude from comparisonTeradata  Xexclude from comparison
DescriptionThe 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.Based on PostgreSQL enhanced with MPP and write-scale-out cluster featuresA hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelDocument store
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
Document store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Websitewww.databricks.comwww.postgres-xl.orgwww.teradata.com
Technical documentationdocs.databricks.comwww.postgres-xl.org/­documentationdocs.teradata.com
DeveloperDatabricksTeradata
Initial release20132014 infosince 2012, originally named StormDB1984
Current release10 R1, October 2018Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourcecommercialOpen Source infoMozilla public licensecommercial
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC
Server operating systemshostedLinux
macOS
hosted
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyes
Typing infopredefined data types such as float or dateyesyes
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 infoXML type, but no XML query functionalityyes
Secondary indexesyesyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLwith Databricks SQLyes infodistributed, parallel query executionyes infoSQL 2016 + extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesPython
R
Scala
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesuser defined functionsyes infoUDFs, stored procedures, table functions in parallel
Triggersyesyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoMVCCACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksPostgres-XLTeradata
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksPostgres-XLTeradata
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