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

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

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Editorial information provided by DB-Engines
NameMemcached  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionIn-memory key-value store, originally intended for cachingA 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
Score19.42
Rank#32  Overall
#4  Key-value stores
Score4.48
Rank#75  Overall
#6  Wide column stores
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websitewww.memcached.orgazure.microsoft.com/­en-us/­services/­storage/­tablessplicemachine.com
Technical documentationgithub.com/­memcached/­memcached/­wikisplicemachine.com/­how-it-works
DeveloperDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalMicrosoftSplice Machine
Initial release200320122014
Current release1.6.25, March 20243.1, March 2021
License infoCommercial or Open SourceOpen Source infoBSD licensecommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCJava
Server operating systemsFreeBSD
Linux
OS X
Unix
Windows
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.no
Secondary indexesnonoyes
SQL infoSupport of SQLnonoyes
APIs and other access methodsProprietary protocolRESTful HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
.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
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud serviceShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoRepcached, a Memcached patch, provides this functionallityyes 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 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 persistentnoyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlyes infousing SASL (Simple Authentication and Security Layer) protocolAccess rights based on private key authentication or shared access signaturesAccess rights for users, groups and roles according to SQL-standard

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MemcachedMicrosoft Azure Table StorageSplice Machine
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