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DBMS > Apache Impala vs. Google Cloud Bigtable vs. LokiJS vs. Microsoft Access vs. Trafodion

System Properties Comparison Apache Impala vs. Google Cloud Bigtable vs. LokiJS vs. Microsoft Access vs. Trafodion

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonLokiJS  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. 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.In-memory JavaScript DBMSMicrosoft 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.)Transactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMSKey-value store
Wide column store
Document storeRelational DBMSRelational DBMS
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
Score0.49
Rank#260  Overall
#42  Document stores
Score101.16
Rank#11  Overall
#8  Relational DBMS
Websiteimpala.apache.orgcloud.google.com/­bigtablegithub.com/­techfort/­LokiJSwww.microsoft.com/­en-us/­microsoft-365/­accesstrafodion.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmlcloud.google.com/­bigtable/­docstechfort.github.io/­LokiJSdeveloper.microsoft.com/­en-us/­accesstrafodion.apache.org/­documentation.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaGoogleMicrosoftApache Software Foundation, originally developed by HP
Initial release20132015201419922014
Current release4.1.0, June 20221902 (16.0.11328.20222), March 20192.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Sourcecommercial infoBundled with Microsoft OfficeOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++JavaScriptC++C++, Java
Server operating systemsLinuxhostedserver-less, requires a JavaScript environment (browser, Node.js)Windows infoNot a real database server, but making use of DLLsLinux
Data schemeyesschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesnonoyesyes
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 indexesyesnoyes infovia viewsyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnonoyes 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)
JavaScript APIADO.NET
DAO
ODBC
OLE DB
ADO.NET
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCC#
C++
Go
Java
JavaScript (Node.js)
Python
JavaScriptC
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reducenoView functions in JavaScriptyes infosince Access 2010 using the ACE-engineJava Stored Procedures
Triggersnonoyesyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnonenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorInternal replication in Colossus, and regional replication between two clusters in different zonesnonenoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesyesnoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)noneImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoAtomic single-row operationsno infoatomic operations within a single collection possibleACID infobut no files for transaction loggingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoSerialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.yes 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.nonoyesno
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)nono infoa simple user-level security was built in till version Access 2003fine grained access rights according to SQL-standard

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More resources
Apache ImpalaGoogle Cloud BigtableLokiJSMicrosoft AccessTrafodion
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