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DBMS > Apache Druid vs. Google Cloud Firestore vs. Microsoft Access vs. Teradata Aster vs. Tkrzw

System Properties Comparison Apache Druid vs. Google Cloud Firestore vs. Microsoft Access vs. Teradata Aster vs. Tkrzw

Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonTeradata Aster  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.
DescriptionOpen-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality dataCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.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.)Platform for big data analytics on multistructured data sources and typesA 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 DBMS
Time Series DBMS
Document storeRelational DBMSRelational DBMSKey-value store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.34
Rank#88  Overall
#48  Relational DBMS
#7  Time Series DBMS
Score7.85
Rank#51  Overall
#8  Document stores
Score104.92
Rank#11  Overall
#8  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitedruid.apache.orgfirebase.google.com/­products/­firestorewww.microsoft.com/­en-us/­microsoft-365/­accessdbmx.net/­tkrzw
Technical documentationdruid.apache.org/­docs/­latest/­designfirebase.google.com/­docs/­firestoredeveloper.microsoft.com/­en-us/­access
DeveloperApache Software Foundation and contributorsGoogleMicrosoftTeradataMikio Hirabayashi
Initial release20122017199220052020
Current release29.0.1, April 20241902 (16.0.11328.20222), March 20190.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercial infoBundled with Microsoft OfficecommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++C++
Server operating systemsLinux
OS X
Unix
hostedWindows infoNot a real database server, but making use of DLLsLinuxLinux
macOS
Data schemeyes infoschema-less columns are supportedschema-freeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeschema-free
Typing infopredefined data types such as float or dateyesyesyesyesno
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 infoin Aster File Storeno
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL for queryingnoyes infobut not compliant to any SQL standardyesno
APIs and other access methodsJDBC
RESTful HTTP/JSON API
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
ADO.NET
DAO
ODBC
OLE DB
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesClojure
JavaScript
PHP
Python
R
Ruby
Scala
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C
C#
C++
Java
Python
R
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnoyes, Firebase Rules & Cloud Functionsyes infosince Access 2010 using the ACE-engineR packagesno
Triggersnoyes, with Cloud Functionsyes infosince Access 2010 using the ACE-enginenono
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingnoneShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyes, via HDFS, S3 or other storage enginesMulti-source replicationnoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud Dataflownoyes infoSQL Map-Reduce Frameworkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACID infobut no files for transaction loggingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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 infousing specific database classes
User concepts infoAccess controlRBAC using LDAP or Druid internals for users and groups for read/write by datasource and systemAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.no infoa simple user-level security was built in till version Access 2003fine grained access rights according to SQL-standardno

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More resources
Apache DruidGoogle Cloud FirestoreMicrosoft AccessTeradata AsterTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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