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

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

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonetcd  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonOpenEdge  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA distributed reliable key-value storeA 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 modelRelational DBMSKey-value storeWide column storeRelational DBMSRelational DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score7.25
Rank#54  Overall
#5  Key-value stores
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
Websiteimpala.apache.orgetcd.io
github.com/­etcd-io/­etcd
azure.microsoft.com/­en-us/­services/­storage/­tableswww.progress.com/­openedgesplicemachine.com
Technical documentationimpala.apache.org/­impala-docs.htmletcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
documentation.progress.com/­output/­ua/­OpenEdge_latestsplicemachine.com/­how-it-works
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaMicrosoftProgress Software CorporationSplice Machine
Initial release2013201219842014
Current release4.1.0, June 20223.4, August 2019OpenEdge 12.2, March 20203.1, March 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercialcommercialOpen 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 languageC++GoJava
Server operating systemsLinuxFreeBSD
Linux
Windows infoexperimental
hostedAIX
HP-UX
Linux
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyesyes
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.nononoyes
Secondary indexesyesnonoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoyes infoclose to SQL 92yes
APIs and other access methodsJDBC
ODBC
gRPC
JSON over HTTP
RESTful HTTP APIJDBC
ODBC
JDBC
Native Spark Datasource
ODBC
Supported programming languagesAll languages supporting JDBC/ODBC.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
Progress proprietary ABL (Advanced Business Language)C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenonoyesyes infoJava
Triggersnoyes, watching key changesnoyesyes
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 nodesselectable replication factorUsing 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.Source-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenononoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonooptimistic 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.nonononoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosnoAccess 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
Apache ImpalaetcdMicrosoft Azure Table StorageOpenEdgeSplice Machine
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