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DBMS > Apache Impala vs. Dolt vs. Fujitsu Enterprise Postgres vs. Microsoft Azure Table Storage

System Properties Comparison Apache Impala vs. Dolt vs. Fujitsu Enterprise Postgres vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDolt  Xexclude from comparisonFujitsu Enterprise Postgres  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopA MySQL compatible DBMS with Git-like versioning of data and schemaEnterprise-grade PostgreSQL-based DBMS with security enhancements such as Transparent Data Encryption and Data Masking, plus high-availability and performance improvement features.A Wide Column Store for rapid development using massive semi-structured datasets
Primary database modelRelational DBMSRelational DBMSRelational DBMSWide column store
Secondary database modelsDocument storeDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.02
Rank#191  Overall
#89  Relational DBMS
Score0.37
Rank#278  Overall
#128  Relational DBMS
Score4.04
Rank#77  Overall
#6  Wide column stores
Websiteimpala.apache.orggithub.com/­dolthub/­dolt
www.dolthub.com
www.postgresql.fastware.comazure.microsoft.com/­en-us/­services/­storage/­tables
Technical documentationimpala.apache.org/­impala-docs.htmldocs.dolthub.comwww.postgresql.fastware.com/­product-manuals
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDoltHub IncPostgreSQL Global Development Group, Fujitsu Australia Software TechnologyMicrosoft
Initial release201320182012
Current release4.1.0, June 2022Fujitsu Enterprise Postgres 14, January 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache Version 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud servicenononoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++GoC
Server operating systemsLinuxLinux
macOS
Windows
Linux
Windows
hosted
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesyes
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.nonono
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyesno
APIs and other access methodsJDBC
ODBC
CLI Client
HTTP REST
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infocurrently in alpha releaseuser defined functionsno
Triggersnoyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingnonepartitioning by range, list and by hashSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorA database can be cloned to multiple locations and be used there in isolation. Data/schema changes can be pushed/pulled explicitly between locations.Source-replica replicationyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosOnly one user is configurable, and must be specified in the config file at startupfine grained access rights according to SQL-standardAccess rights based on private key authentication or shared access signatures

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More resources
Apache ImpalaDoltFujitsu Enterprise PostgresMicrosoft Azure Table Storage
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