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DBMS > Splice Machine vs. Yaacomo

System Properties Comparison Splice Machine vs. Yaacomo

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Editorial information provided by DB-Engines
NameSplice Machine  Xexclude from comparisonYaacomo  Xexclude from comparison
DescriptionOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and SparkOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.80
Rank#193  Overall
#91  Relational DBMS
Score0.00
Rank#354  Overall
#152  Relational DBMS
Websitesplicemachine.comyaacomo.com
Technical documentationdoc.splicemachine.com
DeveloperSplice MachineQ2WEB GmbH
Initial release20142009
Current release3.1, March 2021
License infoCommercial or Open SourceOpen Source infoAGPL 3.0, commercial license availablecommercial
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 languageJava
Server operating systemsLinux
OS X
Solaris
Windows
Android
Linux
Windows
Data schemeyesyes
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 indexesyesyes
SQL infoSupport of SQLyesyes
APIs and other access methodsJDBC
Native Spark Datasource
ODBC
JDBC
ODBC
Supported programming languagesC#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infoJava
Triggersyesyes
Partitioning methods infoMethods for storing different data on different nodesShared Nothhing Auto-Sharding, Columnar Partitioninghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACID
Concurrency infoSupport for concurrent manipulation of datayes, multi-version concurrency control (MVCC)yes
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.yesyes
User concepts infoAccess controlAccess rights for users, groups and roles according to SQL-standardfine grained access rights according to SQL-standard
More information provided by the system vendor
Splice MachineYaacomo
News

How to Break Data Silos to Drive Enterprise-Wide AI
11 June 2021

Point-in-Time Correctness in Machine Learning
1 June 2021

The Compliance Nightmare Lurking in Your Data Science Team
6 May 2021

Whose Job Is It Anyway?
23 April 2021

How Optimizing MLOps Can Revolutionize Enterprise AI
15 April 2021

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More resources
Splice MachineYaacomo
Recent citations in the news

Unified MLOps: Feature Stores and Model Deployment
13 May 2022, InfoQ.com

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

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

Splice Machine Leans on Kubernetes to Manage DBs
3 August 2020, Container Journal

In-memory Data Grid Market Size to Grow by USD 1.51 Billion | Growth of Big Data to Drive Growth| Technavio
16 May 2022, 69News WFMZ-TV

provided by Google News

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