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DBMS > Databricks vs. HBase vs. RDF4J vs. Teradata

System Properties Comparison Databricks vs. HBase vs. RDF4J vs. Teradata

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonHBase  Xexclude from comparisonRDF4J infoformerly known as Sesame  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.Wide-column store based on Apache Hadoop and on concepts of BigTableRDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.A hybrid cloud data analytics software platform (Teradata Vantage)
Primary database modelDocument store
Relational DBMS
Wide column storeRDF storeRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series 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
Score27.97
Rank#26  Overall
#2  Wide column stores
Score0.74
Rank#222  Overall
#9  RDF stores
Score44.87
Rank#22  Overall
#15  Relational DBMS
Websitewww.databricks.comhbase.apache.orgrdf4j.orgwww.teradata.com
Technical documentationdocs.databricks.comhbase.apache.org/­book.htmlrdf4j.org/­documentationdocs.teradata.com
DeveloperDatabricksApache Software Foundation infoApache top-level project, originally developed by PowersetSince 2016 officially forked into an Eclipse project, former developer was Aduna Software.Teradata
Initial release2013200820041984
Current release2.3.4, January 2021Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2Open Source infoEclipse Distribution License (EDL), v1.0.commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava
Server operating systemshostedLinux
Unix
Windows infousing Cygwin
Linux
OS X
Unix
Windows
hosted
Linux
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-free, schema definition possibleyes infoRDF Schemasyes
Typing infopredefined data types such as float or dateoptions 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.yesnoyes
Secondary indexesyesnoyesyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLwith Databricks SQLnonoyes infoSQL 2016 + extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
Java API
RIO infoRDF Input/Output
Sail API
SeRQL infoSesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
Supported programming languagesPython
R
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
Java
PHP
Python
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesyes infoCoprocessors in Javayesyes infoUDFs, stored procedures, table functions in parallel
Triggersyesyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDSingle row ACID (across millions of columns)ACID infoIsolation support depends on the API usedACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoin-memory storage is supported as wellyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABACnofine grained access rights according to SQL-standard
More information provided by the system vendor
DatabricksHBaseRDF4J infoformerly known as SesameTeradata
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksHBaseRDF4J infoformerly known as SesameTeradata
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