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DBMS > Databricks vs. Netezza vs. Stardog vs. WakandaDB

System Properties Comparison Databricks vs. Netezza vs. Stardog vs. WakandaDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonStardog  Xexclude from comparisonWakandaDB  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.Data warehouse and analytics appliance part of IBM PureSystemsEnterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualizationWakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data
Primary database modelDocument store
Relational DBMS
Relational DBMSGraph DBMS
RDF store
Object oriented 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
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score2.02
Rank#123  Overall
#11  Graph DBMS
#6  RDF stores
Score0.03
Rank#364  Overall
#17  Object oriented DBMS
Websitewww.databricks.comwww.ibm.com/­products/­netezzawww.stardog.comwakanda.github.io
Technical documentationdocs.databricks.comdocs.stardog.comwakanda.github.io/­doc
DeveloperDatabricksIBMStardog-UnionWakanda SAS
Initial release2013200020102012
Current release7.3.0, May 20202.7.0 (AprilĀ 29, 2019), April 2019
License infoCommercial or Open Sourcecommercialcommercialcommercial info60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/studentsOpen Source infoAGPLv3, extended commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++, JavaScript
Server operating systemshostedLinux infoincluded in applianceLinux
macOS
Windows
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-free and OWL/RDFS-schema supportyes
Typing infopredefined data types such as float or dateyesyesyes
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.yesno infoImport/export of XML data possibleno
Secondary indexesyesyesyes infosupports real-time indexing in full-text and geospatial
SQL infoSupport of SQLwith Databricks SQLyesYes, compatible with all major SQL variants through dedicated BI/SQL Serverno
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
OLE DB
GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3
RESTful HTTP API
Supported programming languagesPython
R
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby
JavaScript
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesuser defined functions and aggregates, HTTP Server extensions in Javayes
Triggersnoyes infovia event handlersyes
Partitioning methods infoMethods for storing different data on different nodesShardingnonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationMulti-source replication in HA-Clusternone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency in HA-ClusterImmediate Consistency
Foreign keys infoReferential integritynoyes inforelationships in graphs
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID
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.noyesno
User concepts infoAccess controlUsers with fine-grained authorization conceptAccess rights for users and rolesyes
More information provided by the system vendor
DatabricksNetezza infoAlso called PureData System for Analytics by IBMStardogWakandaDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksNetezza infoAlso called PureData System for Analytics by IBMStardogWakandaDB
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