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

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

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Editorial information provided by DB-Engines
NameDatabend  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInfluxDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAn open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexityAutomatically 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
Score0.28
Rank#287  Overall
#131  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score22.12
Rank#28  Overall
#1  Time Series DBMS
Score0.54
Rank#244  Overall
#114  Relational DBMS
Websitegithub.com/­datafuselabs/­databend
www.databend.com
cloud.google.com/­datastorewww.influxdata.com/­products/­influxdb-overviewsplicemachine.com
Technical documentationdocs.databend.comcloud.google.com/­datastore/­docsdocs.influxdata.com/­influxdbsplicemachine.com/­how-it-works
DeveloperDatabend LabsGoogleSplice Machine
Initial release2021200820132014
Current release1.0.59, April 20232.7.6, April 20243.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen 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 languageRustGoJava
Server operating systemshosted
Linux
macOS
hostedLinux
OS X infothrough Homebrew
Linux
OS X
Solaris
Windows
Data schemeyesschema-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 indexesnoyesnoyes
SQL infoSupport of SQLyesSQL-like query language (GQL)SQL-like query languageyes
APIs and other access methodsCLI Client
JDBC
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP API
JSON over UDP
JDBC
Native Spark Datasource
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
Python
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 nodesnoneShardingSharding infoin enterprise version onlyShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-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 integritynoyes infovia ReferenceProperties or Ancestor pathsnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesACID 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.noyes infoDepending on used storage engineyes
User concepts infoAccess controlUsers with fine-grained authorization concept, user rolesAccess 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
DatabendGoogle 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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