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DBMS > Google Cloud Firestore vs. Hazelcast vs. Heroic vs. Linter vs. Teradata Aster

System Properties Comparison Google Cloud Firestore vs. Hazelcast vs. Heroic vs. Linter vs. Teradata Aster

Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonHazelcast  Xexclude from comparisonHeroic  Xexclude from comparisonLinter  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.
DescriptionCloud 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.A widely adopted in-memory data gridTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchRDBMS for high security requirementsPlatform for big data analytics on multistructured data sources and types
Primary database modelDocument storeKey-value storeTime Series DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.85
Rank#51  Overall
#8  Document stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Score0.51
Rank#255  Overall
#21  Time Series DBMS
Score0.09
Rank#346  Overall
#152  Relational DBMS
Websitefirebase.google.com/­products/­firestorehazelcast.comgithub.com/­spotify/­heroiclinter.ru
Technical documentationfirebase.google.com/­docs/­firestorehazelcast.org/­imdg/­docsspotify.github.io/­heroic
DeveloperGoogleHazelcastSpotifyrelex.ruTeradata
Initial release20172008201419902005
Current release5.3.6, November 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJavaC and C++
Server operating systemshostedAll OS with a Java VMAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
Linux
Data schemeschema-freeschema-freeschema-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 dateyesyesyesyesyes
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.noyes infothe object must implement a serialization strategynonoyes infoin Aster File Store
Secondary indexesyesyesyes infovia Elasticsearchyesyes
SQL infoSupport of SQLnoSQL-like query languagenoyesyes
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud Functionsyes infoEvent Listeners, Executor Servicesnoyes infoproprietary syntax with the possibility to convert from PL/SQLR packages
Triggersyes, with Cloud Functionsyes infoEventsnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes infoReplicated MapyesSource-replica replicationyes 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 methodsUsing Cloud Dataflowyesnonoyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesone or two-phase-commit; repeatable reads; read commitednoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Role-based access controlfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Google Cloud FirestoreHazelcastHeroicLinterTeradata Aster
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