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DBMS > Apache Impala vs. Google Cloud Datastore vs. PostgreSQL vs. Tkrzw

System Properties Comparison Apache Impala vs. Google Cloud Datastore vs. PostgreSQL vs. Tkrzw

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonPostgreSQL  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet
Primary database modelRelational DBMSDocument storeRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Key-value store
Secondary database modelsDocument storeDocument store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score4.36
Rank#72  Overall
#12  Document stores
Score636.25
Rank#4  Overall
#4  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websiteimpala.apache.orgcloud.google.com/­datastorewww.postgresql.orgdbmx.net/­tkrzw
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­datastore/­docswww.postgresql.org/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGooglePostgreSQL Global Development Group infowww.postgresql.org/­developerMikio Hirabayashi
Initial release201320081989 info1989: Postgres, 1996: PostgreSQL2020
Current release4.1.0, June 202216.3, May 20240.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoBSDOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++CC++
Server operating systemsLinuxhostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
macOS
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyes, details hereyesno
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.nonoyes infospecific XML-type available, but no XML query functionality.no
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (GQL)yes infostandard with numerous extensionsno
APIs and other access methodsJDBC
ODBC
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
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceusing Google App Engineuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
TriggersnoCallbacks using the Google Apps Engineyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingpartitioning by range, list and (since PostgreSQL 11) by hashnone
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using PaxosSource-replica replication infoother methods possible by using 3rd party extensionsnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual 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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nononoyes infousing specific database classes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standardno

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Apache ImpalaGoogle Cloud DatastorePostgreSQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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