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

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

Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonGigaSpaces  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonOpenEdge  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionA distributed reliable key-value storeHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA Wide Column Store for rapid development using massive semi-structured datasetsApplication development environment with integrated database management systemOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelKey-value storeDocument store
Object oriented DBMS infoValues are user defined objects
Wide column storeRelational DBMSRelational DBMS
Secondary database modelsGraph DBMS
Search engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.25
Rank#54  Overall
#5  Key-value stores
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score4.48
Rank#75  Overall
#6  Wide column stores
Score3.51
Rank#86  Overall
#46  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteetcd.io
github.com/­etcd-io/­etcd
www.gigaspaces.comazure.microsoft.com/­en-us/­services/­storage/­tableswww.progress.com/­openedgesplicemachine.com
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
docs.gigaspaces.com/­latest/­landing.htmldocumentation.progress.com/­output/­ua/­OpenEdge_latestsplicemachine.com/­how-it-works
DeveloperGigaspaces TechnologiesMicrosoftProgress Software CorporationSplice Machine
Initial release2000201219842014
Current release3.4, August 201915.5, September 2020OpenEdge 12.2, March 20203.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache Version 2; Commercial licenses availablecommercialcommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJava, C++, .NetJava
Server operating systemsFreeBSD
Linux
Windows infoexperimental
Linux
macOS
Solaris
Windows
hostedAIX
HP-UX
Linux
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or datenoyesyesyesyes
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 infoXML can be used for describing objects metadatanoyes
Secondary indexesnoyesnoyesyes
SQL infoSupport of SQLnoSQL-99 for query and DML statementsnoyes infoclose to SQL 92yes
APIs and other access methodsgRPC
JSON over HTTP
GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
RESTful HTTP APIJDBC
ODBC
JDBC
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++
Java
Python
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Progress proprietary ABL (Advanced Business Language)C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyesnoyesyes infoJava
Triggersyes, watching key changesyes, event driven architecturenoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicehorizontal partitioning infosince Version 11.4Shared 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.Multi-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
yes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoMap-Reduce pattern can be built with XAP task executorsnonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic lockingACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnonoyes
User concepts infoAccess controlnoRole-based access controlAccess rights based on private key authentication or shared access signaturesUsers and groupsAccess rights for users, groups and roles according to SQL-standard

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More resources
etcdGigaSpacesMicrosoft Azure Table StorageOpenEdgeSplice Machine
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