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DBMS > Databricks vs. GridDB vs. Newts vs. Quasardb

System Properties Comparison Databricks vs. GridDB vs. Newts vs. Quasardb

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGridDB  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.Scalable in-memory time series database optimized for IoT and Big DataTime Series DBMS based on CassandraDistributed, high-performance timeseries database
Primary database modelDocument store
Relational DBMS
Time Series DBMSTime Series DBMSTime Series DBMS
Secondary database modelsKey-value store
Relational 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
Score2.09
Rank#120  Overall
#10  Time Series DBMS
Score0.07
Rank#375  Overall
#41  Time Series DBMS
Score0.21
Rank#322  Overall
#29  Time Series DBMS
Websitewww.databricks.comgriddb.netopennms.github.io/­newtsquasar.ai
Technical documentationdocs.databricks.comdocs.griddb.netgithub.com/­OpenNMS/­newts/­wikidoc.quasar.ai/­master
DeveloperDatabricksToshiba CorporationOpenNMS Groupquasardb
Initial release2013201320142009
Current release5.1, August 20223.14.1, January 2024
License infoCommercial or Open SourcecommercialOpen Source infoAGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also availableOpen 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 serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC++
Server operating systemshostedLinuxLinux
OS X
Windows
BSD
Linux
OS X
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)yesschema-freeschema-free
Typing infopredefined data types such as float or dateyes infonumerical, string, blob, geometry, boolean, timestampyesyes 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 SQLSQL92, SQL-like TQL (Toshiba Query Language)noSQL-like query language
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API
HTTP REST
Java API
HTTP API
Supported programming languagesPython
R
Scala
C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresuser defined functions and aggregatesnonono
Triggersyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding 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 methodsConnector for using GridDB as an input source and output destination for Hadoop MapReduce jobsnowith Hadoop integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency within container, eventual consistency across containersEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID at container levelnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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 controlAccess rights for users can be defined per databasenoCryptographically strong user authentication and audit trail
More information provided by the system vendor
DatabricksGridDBNewtsQuasardb
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
GridDB is a highly scalable, in-memory time series database optimized for IoT and...
» more
Competitive advantages1. Optimized for IoT Equipped with Toshiba's proprietary key-container data model...
» more
Typical application scenariosFactory IoT, Automative Industry, Energy, BEMS, Smart Community, Monitoring system.
» more
Key customersDenso International [see use case ] An Electric Power company [see use case ] Ishinomaki...
» more
Market metricsGitHub trending repository
» more
Licensing and pricing modelsOpen Source license (AGPL v3 & Apache v2) Commercial license (subscription)
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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DatabricksGridDBNewtsQuasardb
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