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DBMS > CockroachDB vs. Google Cloud Datastore vs. InfluxDB vs. Splice Machine

System Properties Comparison CockroachDB vs. Google Cloud Datastore vs. InfluxDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameCockroachDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInfluxDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionCockroachDB is a distributed database architected for modern cloud applications. It is wire compatible with PostgreSQL and backed by a Key-Value Store, which is either RocksDB or a purpose-built derivative, called Pebble.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformDBMS for storing time series, events and metricsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelRelational DBMSDocument storeTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS infowith GEO package
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.73
Rank#58  Overall
#34  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score24.39
Rank#28  Overall
#1  Time Series DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websitewww.cockroachlabs.comcloud.google.com/­datastorewww.influxdata.com/­products/­influxdb-overviewsplicemachine.com
Technical documentationwww.cockroachlabs.com/­docscloud.google.com/­datastore/­docsdocs.influxdata.com/­influxdbsplicemachine.com/­how-it-works
DeveloperCockroach LabsGoogleSplice Machine
Initial release2015200820132014
Current release24.1.0, May 20242.7.6, April 20243.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0, commercial license availablecommercialOpen Source infoMIT-License; commercial enterprise version availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoGoJava
Server operating systemsLinux
macOS
Windows
hostedLinux
OS X infothrough Homebrew
Linux
OS X
Solaris
Windows
Data schemedynamic schemaschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes, 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.nonono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyes, wire compatible with PostgreSQLSQL-like query language (GQL)SQL-like query languageyes
APIs and other access methodsJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
JSON over UDP
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
C++
Clojure
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
.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
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnousing Google App Enginenoyes infoJava
TriggersnoCallbacks using the Google Apps Enginenoyes
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioning (by key range) infoall tables are translated to an ordered KV store and then broken down into 64MB ranges, which are then used as replicas in RAFTShardingSharding infoin enterprise version onlyShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication using RAFTMulti-source replication using Paxosselectable replication factor infoin enterprise version onlyMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infousing Google Cloud DataflownoYes, via Full Spark Integration
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 integrityyesyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
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 controlRole-based access controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)simple rights management via user accountsAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
CockroachDBGoogle Cloud DatastoreInfluxDBSplice Machine
Specific characteristicsInfluxData 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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