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

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

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonFatDB  Xexclude from comparisonHBase  Xexclude from comparisonJanusGraph infosuccessor of Titan  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 .NET NoSQL DBMS that can integrate with and extend SQL Server.Wide-column store based on Apache Hadoop and on concepts of BigTableA Graph DBMS optimized for distributed clusters infoIt was forked from the latest code base of Titan in January 2017NewSQL database with distributed OLTP and SQL
Primary database modelDocument store
Relational DBMS
Document store
Key-value store
Wide column storeGraph DBMSDocument 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
Score30.50
Rank#26  Overall
#2  Wide column stores
Score1.94
Rank#129  Overall
#12  Graph DBMS
Score0.45
Rank#261  Overall
#41  Document stores
#122  Relational DBMS
Websitewww.databricks.comhbase.apache.orgjanusgraph.orgwww.sequoiadb.com
Technical documentationdocs.databricks.comhbase.apache.org/­book.htmldocs.janusgraph.orgwww.sequoiadb.com/­en/­index.php?m=Files&a=index
DeveloperDatabricksFatCloudApache Software Foundation infoApache top-level project, originally developed by PowersetLinux Foundation; originally developed as Titan by AureliusSequoiadb Ltd.
Initial release20132012200820172013
Current release2.3.4, January 20210.6.3, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache version 2Open Source infoApache 2.0Open Source infoServer: AGPL; Client: Apache V2
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC#JavaJavaC++
Server operating systemshostedWindowsLinux
Unix
Windows infousing Cygwin
Linux
OS X
Unix
Windows
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free, schema definition possibleyesschema-free
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVROyesyes 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 indexesyesyesnoyesyes
SQL infoSupport of SQLwith Databricks SQLno infoVia inetgration in SQL ServernonoSQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
Java API
RESTful HTTP API
Thrift
Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster
proprietary protocol using JSON
Supported programming languagesPython
R
Scala
C#C
C#
C++
Groovy
Java
PHP
Python
Scala
Clojure
Java
Python
.Net
C++
Java
PHP
Python
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infovia applicationsyes infoCoprocessors in JavayesJavaScript
Triggersyes infovia applicationsyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes infodepending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorMulti-source replication
Source-replica replication
yesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyes infovia Faunus, a graph analytics engineno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Foreign keys infoReferential integritynonoyes infoRelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoSingle row ACID (across millions of columns)ACIDDocument is locked during a transaction
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoSupports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcastyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesno
User concepts infoAccess controlno infoCan implement custom security layer via applicationsAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACUser authentification and security via Rexster Graph Serversimple password-based access control
More information provided by the system vendor
DatabricksFatDBHBaseJanusGraph infosuccessor of TitanSequoiadb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksFatDBHBaseJanusGraph infosuccessor of TitanSequoiadb
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