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DBMS > etcd vs. Microsoft Azure Table Storage vs. Splice Machine

System Properties Comparison etcd vs. Microsoft Azure Table Storage vs. Splice Machine

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionA distributed reliable key-value storeA Wide Column Store for rapid development using massive semi-structured datasetsOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeWide column storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.64
Rank#54  Overall
#5  Key-value stores
Score4.92
Rank#73  Overall
#6  Wide column stores
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
azure.microsoft.com/­en-us/­services/­storage/­tablessplicemachine.com
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
splicemachine.com/­how-it-works
DeveloperMicrosoftSplice Machine
Initial release20122014
Current release3.4, August 20193.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJava
Server operating systemsFreeBSD
Linux
Windows infoexperimental
hostedLinux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or datenoyesyes
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.nono
Secondary indexesnonoyes
SQL infoSupport of SQLnonoyes
APIs and other access methodsgRPC
JSON over HTTP
RESTful HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes infoJava
Triggersyes, watching key changesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanooptimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlnoAccess rights based on private key authentication or shared access signaturesAccess rights for users, groups and roles according to SQL-standard

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More resources
etcdMicrosoft Azure Table StorageSplice Machine
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