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DBMS > Apache Impala vs. EDB Postgres vs. Google Cloud Datastore vs. Postgres-XL

System Properties Comparison Apache Impala vs. EDB Postgres vs. Google Cloud Datastore vs. Postgres-XL

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonEDB Postgres  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopThe EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelRelational DBMSRelational DBMSDocument storeRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score1.91
Rank#130  Overall
#60  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score0.53
Rank#254  Overall
#117  Relational DBMS
Websiteimpala.apache.orgwww.enterprisedb.comcloud.google.com/­datastorewww.postgres-xl.org
Technical documentationimpala.apache.org/­impala-docs.htmlwww.enterprisedb.com/­docscloud.google.com/­datastore/­docswww.postgres-xl.org/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaEnterpriseDBGoogle
Initial release2013200520082014 infosince 2012, originally named StormDB
Current release4.1.0, June 202214, December 202110 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infoBSD for PostgreSQL-componentscommercialOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CC
Server operating systemsLinuxLinux
Windows
hostedLinux
macOS
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyes
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.noyes infospecific XML-type available, but no XML query functionality.noyes infoXML type, but no XML query functionality
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infostandard with numerous extensionsSQL-like query language (GQL)yes infodistributed, parallel query execution
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesAll languages supporting JDBC/ODBC.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.using Google App Engineuser defined functions
TriggersnoyesCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoby hash, list or rangeShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replicationMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integritynoyesyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyes
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.nononono
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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More resources
Apache ImpalaEDB PostgresGoogle Cloud DatastorePostgres-XL
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