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DBMS > Databricks vs. etcd vs. FatDB vs. HBase vs. Sequoiadb

System Properties Comparison Databricks vs. etcd vs. FatDB vs. HBase vs. Sequoiadb

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonetcd  Xexclude from comparisonFatDB  Xexclude from comparisonHBase  Xexclude from comparisonSequoiadb  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
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 storeA .NET NoSQL DBMS that can integrate with and extend SQL Server.Wide-column store based on Apache Hadoop and on concepts of BigTableNewSQL database with distributed OLTP and SQL
Primary database modelDocument store
Relational DBMS
Key-value storeDocument store
Key-value store
Wide column storeDocument store
Relational 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
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Websitewww.databricks.cometcd.io
github.com/­etcd-io/­etcd
hbase.apache.orgwww.sequoiadb.com
Technical documentationdocs.databricks.cometcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
hbase.apache.org/­book.htmlwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperDatabricksFatCloudApache Software Foundation infoApache top-level project, originally developed by PowersetSequoiadb Ltd.
Initial release2013201220082013
Current release3.4, August 20192.3.4, January 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0commercialOpen Source infoApache version 2Open Source infoServer: AGPL; Client: Apache V2
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 languageGoC#JavaC++
Server operating systemshostedFreeBSD
Linux
Windows infoexperimental
WindowsLinux
Unix
Windows infousing Cygwin
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeschema-free, schema definition possibleschema-free
Typing infopredefined data types such as float or datenoyesoptions to bring your own types, AVROyes infooid, date, timestamp, binary, regex
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 indexesyesnoyesnoyes
SQL infoSupport of SQLwith Databricks SQLnono infoVia inetgration in SQL ServernoSQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC
JSON over HTTP
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Java API
RESTful HTTP API
Thrift
proprietary protocol using JSON
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#
C++
Groovy
Java
PHP
Python
Scala
.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesnoyes infovia applicationsyes infoCoprocessors in JavaJavaScript
Triggersyes, watching key changesyes infovia applicationsyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.selectable replication factorMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonoSingle row ACID (across millions of columns)Document is locked during a transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nonoyesno
User concepts infoAccess controlnono infoCan implement custom security layer via applicationsAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACsimple password-based access control
More information provided by the system vendor
DatabricksetcdFatDBHBaseSequoiadb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksetcdFatDBHBaseSequoiadb
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