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DBMS > Databricks vs. Netezza vs. Newts vs. RavenDB

System Properties Comparison Databricks vs. Netezza vs. Newts vs. RavenDB

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonNewts  Xexclude from comparisonRavenDB  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 PureSystemsTime Series DBMS based on CassandraOpen Source Operational and Transactional Enterprise NoSQL Document Database
Primary database modelDocument store
Relational DBMS
Relational DBMSTime Series DBMSDocument store
Secondary database modelsGraph 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
Score8.59
Rank#45  Overall
#29  Relational DBMS
Score0.07
Rank#375  Overall
#41  Time Series DBMS
Score2.84
Rank#101  Overall
#18  Document stores
Websitewww.databricks.comwww.ibm.com/­products/­netezzaopennms.github.io/­newtsravendb.net
Technical documentationdocs.databricks.comgithub.com/­OpenNMS/­newts/­wikiravendb.net/­docs
DeveloperDatabricksIBMOpenNMS GroupHibernating Rhinos
Initial release2013200020142010
Current release5.4, July 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoAGPL version 3, 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#
Server operating systemshostedLinux infoincluded in applianceLinux
OS X
Windows
Linux
macOS
Raspberry Pi
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesno
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
Secondary indexesyesyesnoyes
SQL infoSupport of SQLwith Databricks SQLyesnoSQL-like query language (RQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
OLE DB
HTTP REST
Java API
.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API
Supported programming languagesPython
R
Scala
C
C++
Fortran
Java
Lua
Perl
Python
R
Java.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functions and aggregatesyesnoyes
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infobased on CassandraSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationselectable replication factor infobased on CassandraMulti-source replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoACID, Cluster-wide transaction available
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.nono
User concepts infoAccess controlUsers with fine-grained authorization conceptnoAuthorization levels configured per client per database
More information provided by the system vendor
DatabricksNetezza infoAlso called PureData System for Analytics by IBMNewtsRavenDB
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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