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DBMS > Databricks vs. Riak KV vs. Stardog vs. VelocityDB

System Properties Comparison Databricks vs. Riak KV vs. Stardog vs. VelocityDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonRiak KV  Xexclude from comparisonStardog  Xexclude from comparisonVelocityDB  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.Distributed, fault tolerant key-value storeEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationA .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)
Primary database modelDocument store
Relational DBMS
Key-value store infowith links between data sets and object tags for the creation of secondary indexesGraph DBMS
RDF store
Graph DBMS
Object oriented 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
Score4.01
Rank#79  Overall
#9  Key-value stores
Score2.07
Rank#122  Overall
#11  Graph DBMS
#6  RDF stores
Score0.11
Rank#354  Overall
#37  Graph DBMS
#15  Object oriented DBMS
Websitewww.databricks.comwww.stardog.comvelocitydb.com
Technical documentationdocs.databricks.comwww.tiot.jp/­riak-docs/­riak/­kv/­latestdocs.stardog.comvelocitydb.com/­UserGuide
DeveloperDatabricksOpenSource, formerly Basho TechnologiesStardog-UnionVelocityDB Inc
Initial release2013200920102011
Current release3.2.0, December 20227.3.0, May 20207.x
License infoCommercial or Open SourcecommercialOpen Source infoApache version 2, commercial enterprise editioncommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentscommercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageErlangJavaC#
Server operating systemshostedLinux
OS X
Linux
macOS
Windows
Any that supports .NET
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-free and OWL/RDFS-schema supportyes
Typing infopredefined data types such as float or datenoyesyes
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.yesnono infoImport/export of XML data possibleno
Secondary indexesyesrestrictedyes infosupports real-time indexing in full-text and geospatialyes
SQL infoSupport of SQLwith Databricks SQLnoYes, compatible with all major SQL variants through dedicated BI/SQL Serverno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
HTTP API
Native Erlang Interface
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
.Net
Supported programming languagesPython
R
Scala
C infounofficial client library
C#
C++ infounofficial client library
Clojure infounofficial client library
Dart infounofficial client library
Erlang
Go infounofficial client library
Groovy infounofficial client library
Haskell infounofficial client library
Java
JavaScript infounofficial client library
Lisp infounofficial client library
Perl infounofficial client library
PHP
Python
Ruby
Scala infounofficial client library
Smalltalk infounofficial client library
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
.Net
Server-side scripts infoStored proceduresuser defined functions and aggregatesErlanguser defined functions and aggregates, HTTP Server extensions in Javano
Triggersyes infopre-commit hooks and post-commit hooksyes infovia event handlersCallbacks are triggered when data changes
Partitioning methods infoMethods for storing different data on different nodesSharding infono "single point of failure"noneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorMulti-source replication in HA-Cluster
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency in HA-ClusterImmediate Consistency
Foreign keys infoReferential integrityno infolinks between data sets can be storedyes inforelationships in graphsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlyes, using Riak SecurityAccess rights for users and rolesBased on Windows Authentication
More information provided by the system vendor
DatabricksRiak KVStardogVelocityDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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DatabricksRiak KVStardogVelocityDB
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