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

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

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Editorial information provided by DB-Engines
NameApache Druid  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonTeradata Aster  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 types
Primary database modelRelational DBMS
Time Series DBMS
Document storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score3.33
Rank#99  Overall
#51  Relational DBMS
#7  Time Series DBMS
Score9.97
Rank#47  Overall
#8  Document stores
Score107.93
Rank#11  Overall
#8  Relational DBMS
Websitedruid.apache.orgfirebase.google.com/­products/­firestorewww.microsoft.com/­en-us/­microsoft-365/­access
Technical documentationdruid.apache.org/­docs/­latest/­designfirebase.google.com/­docs/­firestoredeveloper.microsoft.com/­en-us/­access
DeveloperApache Software Foundation and contributorsGoogleMicrosoftTeradata
Initial release2012201719922005
Current release29.0.0, February 20241902 (16.0.11328.20222), March 2019
License infoCommercial or Open SourceOpen Source infoApache license v2commercialcommercial infoBundled with Microsoft Officecommercial
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemsLinux
OS X
Unix
hostedWindows infoNot a real database server, but making use of DLLsLinux
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 Store
Typing infopredefined data types such as float or dateyesyesyesyes
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 Store
Secondary indexesyesyesyesyes
SQL infoSupport of SQLSQL for queryingnoyes infobut not compliant to any SQL standardyes
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
Server-side scripts infoStored proceduresnoyes, Firebase Rules & Cloud Functionsyes infosince Access 2010 using the ACE-engineR packages
Triggersnoyes, with Cloud Functionsyes infosince Access 2010 using the ACE-engineno
Partitioning methods infoMethods for storing different data on different nodesSharding infomanual/auto, time-basedShardingnoneSharding
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.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud Dataflownoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynonoyesno
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 datayesyesyesyes
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.nono
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-standard

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More resources
Apache DruidGoogle Cloud FirestoreMicrosoft AccessTeradata Aster
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