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DBMS > Databricks vs. Graph Engine vs. Netezza vs. Newts vs. Quasardb

System Properties Comparison Databricks vs. Graph Engine vs. Netezza vs. Newts vs. Quasardb

Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGraph Engine infoformer name: Trinity  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonNewts  Xexclude from comparisonQuasardb  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.A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engineData warehouse and analytics appliance part of IBM PureSystemsTime Series DBMS based on CassandraDistributed, high-performance timeseries database
Primary database modelDocument store
Relational DBMS
Graph DBMS
Key-value store
Relational DBMSTime Series DBMSTime Series 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
Score0.61
Rank#240  Overall
#21  Graph DBMS
#35  Key-value stores
Score9.06
Rank#46  Overall
#29  Relational DBMS
Score0.00
Rank#383  Overall
#41  Time Series DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Websitewww.databricks.comwww.graphengine.iowww.ibm.com/­products/­netezzaopennms.github.io/­newtsquasar.ai
Technical documentationdocs.databricks.comwww.graphengine.io/­docs/­manualgithub.com/­OpenNMS/­newts/­wikidoc.quasar.ai/­master
DeveloperDatabricksMicrosoftIBMOpenNMS Groupquasardb
Initial release20132010200020142009
Current release3.14.1, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoMIT LicensecommercialOpen Source infoApache 2.0commercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licenses
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation language.NET and CJavaC++
Server operating systemshosted.NETLinux infoincluded in applianceLinux
OS X
Windows
BSD
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesyesyes infointeger and binary
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 indexesyesyesnoyes infowith tags
SQL infoSupport of SQLwith Databricks SQLnoyesnoSQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
OLE DB
HTTP REST
Java API
HTTP API
Supported programming languagesPython
R
Scala
C#
C++
F#
Visual Basic
C
C++
Fortran
Java
Lua
Perl
Python
R
Java.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesyesnono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningShardingSharding infobased on CassandraSharding infoconsistent hashing
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationselectable replication factor infobased on CassandraSource-replica replication with selectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesoptional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storageyesyesyes infoby using LevelDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes infoTransient mode
User concepts infoAccess controlUsers with fine-grained authorization conceptnoCryptographically strong user authentication and audit trail
More information provided by the system vendor
DatabricksGraph Engine infoformer name: TrinityNetezza infoAlso called PureData System for Analytics by IBMNewtsQuasardb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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More resources
DatabricksGraph Engine infoformer name: TrinityNetezza infoAlso called PureData System for Analytics by IBMNewtsQuasardb
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