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DBMS > Databricks vs. Heroic vs. Postgres-XL

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

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHeroic  Xexclude from comparisonPostgres-XL  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.Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelDocument store
Relational DBMS
Time Series DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score81.08
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score0.53
Rank#254  Overall
#117  Relational DBMS
Websitewww.databricks.comgithub.com/­spotify/­heroicwww.postgres-xl.org
Technical documentationdocs.databricks.comspotify.github.io/­heroicwww.postgres-xl.org/­documentation
DeveloperDatabricksSpotify
Initial release201320142014 infosince 2012, originally named StormDB
Current release10 R1, October 2018
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoMozilla public license
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC
Server operating systemshostedLinux
macOS
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeyes
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.yesnoyes infoXML type, but no XML query functionality
Secondary indexesyesyes infovia Elasticsearchyes
SQL infoSupport of SQLwith Databricks SQLnoyes infodistributed, parallel query execution
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesPython
R
Scala
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesnouser defined functions
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID infoMVCC
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.nonono
User concepts infoAccess controlfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksHeroicPostgres-XL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksHeroicPostgres-XL
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