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DBMS > Heroic vs. Splice Machine

System Properties Comparison Heroic vs. Splice Machine

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Editorial information provided by DB-Engines
NameHeroic  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelTime Series DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.09
Rank#309  Overall
#27  Time Series DBMS
Score0.87
Rank#188  Overall
#90  Relational DBMS
Websitespotify.github.io/­heroic/­#!/­indexsplicemachine.com
Technical documentationspotify.github.io/­heroic/­#!/­docs/­overviewdoc.splicemachine.com
DeveloperSpotifySplice Machine
Initial release20142014
Current release3.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaJava
Server operating systemsLinux
OS X
Solaris
Windows
Data schemeschema-freeyes
Typing infopredefined data types such as float or dateyesyes
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.no
Secondary indexesyes infovia Elasticsearchyes
SQL infoSupport of SQLnoyes
APIs and other access methodsHQL (Heroic Query Language, a JSON-based language)
HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languagesC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infoJava
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
HeroicSplice Machine
News

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11 June 2021

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1 June 2021

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6 May 2021

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23 April 2021

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15 April 2021

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More resources
HeroicSplice Machine
Recent citations in the news

Splice Machine Announces New Capabilities to Support Real-Time AI with Version 3.1 of its Scale-Out SQL Database
9 March 2021, PRNewswire

Splice Machine Launches the Splice Machine Feature Store to Simplify Feature Engineering and Democratize Machine Learning
19 January 2021, PRNewswire

Machine learning data pipeline outfit Splice Machine files for insolvency
26 August 2021, The Register

Splice Machine database travels full circle to predictive application platform
25 September 2017, ZDNet

Splice Machine Introduces New Edition of Livewire Operational AI Platform for Industrial Users
25 May 2021, PRNewswire

provided by Google News



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