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DBMS > Databricks vs. Google Cloud Datastore vs. InfluxDB vs. MySQL

System Properties Comparison Databricks vs. Google Cloud Datastore vs. InfluxDB vs. MySQL

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Editorial information provided by DB-Engines
NameDatabricks  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInfluxDB  Xexclude from comparisonMySQL  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.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDBMS for storing time series, events and metricsWidely used open source RDBMS
Primary database modelDocument store
Relational DBMS
Document storeTime Series DBMSRelational DBMS infoKey/Value like access via memcached API
Secondary database modelsSpatial DBMS infowith GEO packageDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score84.24
Rank#14  Overall
#2  Document stores
#9  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score22.12
Rank#28  Overall
#1  Time Series DBMS
Score1029.49
Rank#2  Overall
#2  Relational DBMS
Websitewww.databricks.comcloud.google.com/­datastorewww.influxdata.com/­products/­influxdb-overviewwww.mysql.com
Technical documentationdocs.databricks.comcloud.google.com/­datastore/­docsdocs.influxdata.com/­influxdbdev.mysql.com/­doc
DeveloperDatabricksGoogleOracle infosince 2010, originally MySQL AB, then Sun
Initial release2013200820131995
Current release2.7.6, April 20249.0.0, July 2024
License infoCommercial or Open SourcecommercialcommercialOpen Source infoMIT-License; commercial enterprise version availableOpen Source infoGPL version 2. Commercial licenses with extended functionallity are available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC and C++
Server operating systemshostedhostedLinux
OS X infothrough Homebrew
FreeBSD
Linux
OS X
Solaris
Windows
Data schemeFlexible Schema (defined schema, partial schema, schema free)schema-freeschema-freeyes
Typing infopredefined data types such as float or dateyes, details hereNumeric data and Stringsyes
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.yesnonoyes
Secondary indexesyesyesnoyes
SQL infoSupport of SQLwith Databricks SQLSQL-like query language (GQL)SQL-like query languageyes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
JSON over UDP
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesPython
R
Scala
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions and aggregatesusing Google App Enginenoyes infoproprietary syntax
TriggersCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoin enterprise version onlyhorizontal partitioning, sharding with MySQL Cluster or MySQL Fabric
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosselectable replication factor infoin enterprise version onlyMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integrityyes infovia ReferenceProperties or Ancestor pathsnoyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID infonot for MyISAM storage engine
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
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.nonoyes infoDepending on used storage engineyes
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)simple rights management via user accountsUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
DatabricksGoogle Cloud DatastoreInfluxDBMySQL
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
» more
InfluxData is the creator of InfluxDB , the open source time series database. It...
» more
Competitive advantagesTime to Value InfluxDB is available in all the popular languages and frameworks,...
» more
Typical application scenariosIoT & Sensor Monitoring Developers are witnessing the instrumentation of every available...
» more
Key customersInfluxData has more than 1,900 paying customers, including customers include MuleSoft,...
» more
Market metricsFastest-growing database to drive 27,500 GitHub stars Over 750,000 daily active instances
» more
Licensing and pricing modelsOpen source core with closed source clustering available either on-premise or on...
» more
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