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DBMS > Google Cloud Firestore vs. Hazelcast vs. Manticore Search vs. TDengine

System Properties Comparison Google Cloud Firestore vs. Hazelcast vs. Manticore Search vs. TDengine

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Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonHazelcast  Xexclude from comparisonManticore Search  Xexclude from comparisonTDengine  Xexclude from comparison
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 gridMulti-storage database for search, including full-text search.Time Series DBMS and big data platform
Primary database modelDocument storeKey-value storeSearch engineTime Series DBMS
Secondary database modelsDocument store infoJSON support with IMDG 3.12Time Series DBMS infousing the Manticore Columnar LibraryRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.36
Rank#53  Overall
#9  Document stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.29
Rank#302  Overall
#21  Search engines
Score2.68
Rank#106  Overall
#9  Time Series DBMS
Websitefirebase.google.com/­products/­firestorehazelcast.commanticoresearch.comgithub.com/­taosdata/­TDengine
tdengine.com
Technical documentationfirebase.google.com/­docs/­firestorehazelcast.org/­imdg/­docsmanual.manticoresearch.comdocs.tdengine.com
DeveloperGoogleHazelcastManticore SoftwareTDEngine, previously Taos Data
Initial release2017200820172019
Current release5.3.6, November 20236.0, February 20233.0, August 2022
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availableOpen Source infoGPL version 2Open Source infoAGPL V3, also commercial editions available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++C
Server operating systemshostedAll OS with a Java VMFreeBSD
Linux
macOS
Windows
Linux
Windows
Data schemeschema-freeschema-freeFixed schemayes
Typing infopredefined data types such as float or dateyesyesInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Booleanyes
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 strategyCan index from XMLno
Secondary indexesyesyesyes infofull-text index on all search fieldsno
SQL infoSupport of SQLnoSQL-like query languageSQL-like query languageStandard SQL with extensions for time-series applications
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
JDBC
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud Functionsyes infoEvent Listeners, Executor Servicesuser defined functionsno
Triggersyes, with Cloud Functionsyes infoEventsnoyes, via alarm monitoring
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supportedSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes infoReplicated MapSynchronous replication based on Galera libraryyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud Dataflowyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus Algorithm
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesone or two-phase-commit; repeatable reads; read commitedyes infoisolated transactions for atomic changes and binary logging for safe writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Manticore index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
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 controlnoyes
More information provided by the system vendor
Google Cloud FirestoreHazelcastManticore SearchTDengine
Specific characteristicsTDengineā„¢ is a next generation data historian purpose-built for Industry 4.0 and...
» more
Competitive advantagesHigh Performance at any Scale: TDengine is purpose-built for handling massive industrial...
» more
Typical application scenariosTDengine is designed for Industrial IoT scenarios, including: Manufacturing Connected...
» more
Market metricsTDengine has garnered over 22,500 stars on GitHub and is used in over 50 countries...
» more
Licensing and pricing modelsTDengine OSS is an open source, cloud native time series database. It includes built-in...
» more
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