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DBMS > Apache Impala vs. Google Cloud Bigtable vs. Microsoft Access vs. NuoDB vs. ToroDB

System Properties Comparison Apache Impala vs. Google Cloud Bigtable vs. Microsoft Access vs. NuoDB vs. ToroDB

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonNuoDB  Xexclude from comparisonToroDB  Xexclude from comparison
ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAnalytic DBMS for HadoopGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Microsoft 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.)NuoDB is a webscale distributed database that supports SQL and ACID transactionsA MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelRelational DBMSKey-value store
Wide column store
Relational DBMSRelational DBMSDocument store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score12.45
Rank#40  Overall
#24  Relational DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score101.16
Rank#11  Overall
#8  Relational DBMS
Score0.94
Rank#197  Overall
#92  Relational DBMS
Websiteimpala.apache.orgcloud.google.com/­bigtablewww.microsoft.com/­en-us/­microsoft-365/­accesswww.3ds.com/­nuodb-distributed-sql-databasegithub.com/­torodb/­server
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­bigtable/­docsdeveloper.microsoft.com/­en-us/­accessdoc.nuodb.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleMicrosoftDassault Systèmes infooriginally NuoDB, Inc.8Kdata
Initial release20132015199220132016
Current release4.1.0, June 20221902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialcommercial infoBundled with Microsoft Officecommercial infolimited edition freeOpen Source infoAGPL-V3
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++C++Java
Server operating systemsLinuxhostedWindows infoNot a real database server, but making use of DLLshosted infoAmazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows
All OS with a Java 7 VM
Data schemeyesschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesnoyesyesyes infostring, integer, double, boolean, date, object_id
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.nononono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infobut not compliant to any SQL standardyes
APIs and other access methodsJDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
ADO.NET
DAO
ODBC
OLE DB
ADO.NET
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
.Net
C
C++
Go
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoyes infosince Access 2010 using the ACE-engineJava, SQL
Triggersnonoyes infosince Access 2010 using the ACE-engineyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonedata is dynamically stored/cached on the nodes where it is read/writtenSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesnoneyes infoManaged transparently by NuoDBSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynonoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsACID infobut no files for transaction loggingACID infotunable commit protocolno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMVCCyes
Durability infoSupport for making data persistentyesyesyes infobut no files for transaction loggingyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes infoTemporary table
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 2003Standard SQL roles/ privileges, Administrative UsersAccess rights for users and roles

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More resources
Apache ImpalaGoogle Cloud BigtableMicrosoft AccessNuoDBToroDB
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