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DBMS > Apache Impala vs. Google Cloud Datastore vs. Microsoft Access vs. RethinkDB

System Properties Comparison Apache Impala vs. Google Cloud Datastore vs. Microsoft Access vs. RethinkDB

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonRethinkDB  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)DBMS for the Web with a mechanism to push updated query results to applications in realtime.
Primary database modelRelational DBMSDocument storeRelational DBMSDocument store
Secondary database modelsDocument storeSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score4.13
Rank#71  Overall
#12  Document stores
Score93.76
Rank#12  Overall
#8  Relational DBMS
Score2.58
Rank#105  Overall
#20  Document stores
Websiteimpala.apache.orgcloud.google.com/­datastorewww.microsoft.com/­en-us/­microsoft-365/­accessrethinkdb.com
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­datastore/­docsdeveloper.microsoft.com/­en-us/­accessrethinkdb.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleMicrosoftThe Linux Foundation infosince July 2017
Initial release2013200819922009
Current release4.1.0, June 20221902 (16.0.11328.20222), March 20192.4.1, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infoBundled with Microsoft OfficeOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C++
Server operating systemsLinuxhostedWindows infoNot a real database server, but making use of DLLsLinux
OS X
Windows
Data schemeyesschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyes, details hereyesyes infostring, binary, float, bool, date, geometry
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 indexesyesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (GQL)yes infobut not compliant to any SQL standardno
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
ADO.NET
DAO
ODBC
OLE DB
Supported programming languagesAll languages supporting JDBC/ODBC.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C infocommunity-supported driver
C# infocommunity-supported driver
C++ infocommunity-supported driver
Clojure infocommunity-supported driver
Dart infocommunity-supported driver
Erlang infocommunity-supported driver
Go infocommunity-supported driver
Haskell infocommunity-supported driver
Java infoofficial driver
JavaScript (Node.js) infoofficial driver
Lisp infocommunity-supported driver
Lua infocommunity-supported driver
Objective-C infocommunity-supported driver
Perl infocommunity-supported driver
PHP infocommunity-supported driver
Python infoofficial driver
Ruby infoofficial driver
Scala infocommunity-supported driver
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceusing Google App Engineyes infosince Access 2010 using the ACE-engine
TriggersnoCallbacks using the Google Apps Engineyes infosince Access 2010 using the ACE-engineClient-side triggers through changefeeds
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnoneSharding inforange based
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-source replication using PaxosnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes infousing Google Cloud Dataflownoyes
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 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 infobut no files for transaction loggingAtomic single-document operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMVCC based
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonono
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)no infoa simple user-level security was built in till version Access 2003yes infousers and table-level permissions

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More resources
Apache ImpalaGoogle Cloud DatastoreMicrosoft AccessRethinkDB
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