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DBMS > Databricks vs. etcd vs. HBase vs. Heroic vs. Valentina Server

System Properties Comparison Databricks vs. etcd vs. HBase vs. Heroic vs. Valentina Server

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonetcd  Xexclude from comparisonHBase  Xexclude from comparisonHeroic  Xexclude from comparisonValentina Server  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.A distributed reliable key-value storeWide-column store based on Apache Hadoop and on concepts of BigTableTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchObject-relational database and reports server
Primary database modelDocument store
Relational DBMS
Key-value storeWide column storeTime Series DBMSRelational 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
Score7.25
Rank#54  Overall
#5  Key-value stores
Score30.50
Rank#26  Overall
#2  Wide column stores
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitewww.databricks.cometcd.io
github.com/­etcd-io/­etcd
hbase.apache.orggithub.com/­spotify/­heroicwww.valentina-db.net
Technical documentationdocs.databricks.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
hbase.apache.org/­book.htmlspotify.github.io/­heroicvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperDatabricksApache Software Foundation infoApache top-level project, originally developed by PowersetSpotifyParadigma Software
Initial release2013200820141999
Current release3.4, August 20192.3.4, January 20215.7.5
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache version 2Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJavaJava
Server operating systemshostedFreeBSD
Linux
Windows infoexperimental
Linux
Unix
Windows infousing Cygwin
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free, schema definition possibleschema-freeyes
Typing infopredefined data types such as float or datenooptions to bring your own types, AVROyesyes
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.yesnonono
Secondary indexesyesnonoyes infovia Elasticsearchyes
SQL infoSupport of SQLwith Databricks SQLnononoyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC
JSON over HTTP
Java API
RESTful HTTP API
Thrift
HQL (Heroic Query Language, a JSON-based language)
HTTP API
ODBC
Supported programming languagesPython
R
Scala
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
C
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes infoCoprocessors in Javanoyes
Triggersyes, watching key changesyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replication
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoSingle row ACID (across millions of columns)no
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nonoyesnoyes
User concepts infoAccess controlnoAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACfine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksetcdHBaseHeroicValentina Server
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksetcdHBaseHeroicValentina Server
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