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DBMS > etcd vs. Firebase Realtime Database vs. Google Cloud Datastore vs. Manticore Search

System Properties Comparison etcd vs. Firebase Realtime Database vs. Google Cloud Datastore vs. Manticore Search

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Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonManticore Search  Xexclude from comparison
DescriptionA distributed reliable key-value storeCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformMulti-storage database for search, including full-text search.
Primary database modelKey-value storeDocument storeDocument storeSearch engine
Secondary database modelsTime Series DBMS infousing the Manticore Columnar Library
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.03
Rank#54  Overall
#5  Key-value stores
Score13.64
Rank#39  Overall
#6  Document stores
Score4.36
Rank#72  Overall
#12  Document stores
Score0.29
Rank#302  Overall
#21  Search engines
Websiteetcd.io
github.com/­etcd-io/­etcd
firebase.google.com/­products/­realtime-databasecloud.google.com/­datastoremanticoresearch.com
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
firebase.google.com/­docs/­databasecloud.google.com/­datastore/­docsmanual.manticoresearch.com
DeveloperGoogle infoacquired by Google 2014GoogleManticore Software
Initial release201220082017
Current release3.4, August 20196.0, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialcommercialOpen Source infoGPL version 2
Cloud-based only infoOnly available as a cloud servicenoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoC++
Server operating systemsFreeBSD
Linux
Windows infoexperimental
hostedhostedFreeBSD
Linux
macOS
Windows
Data schemeschema-freeschema-freeschema-freeFixed schema
Typing infopredefined data types such as float or datenoyesyes, details hereInt, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean
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.nononoCan index from XML
Secondary indexesnoyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnonoSQL-like query language (GQL)SQL-like query language
APIs and other access methodsgRPC
JSON over HTTP
Android
iOS
JavaScript API
RESTful HTTP API
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Java
JavaScript
Objective-C
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Server-side scripts infoStored proceduresnolimited functionality with using 'rules'using Google App Engineuser defined functions
Triggersyes, watching key changesCallbacks are triggered when data changesCallbacks using the Google Apps Engineno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesUsing Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.Multi-source replication using PaxosSynchronous replication based on Galera library
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.
Foreign keys infoReferential integritynonoyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACID infoSerializable Isolation within Transactions, Read Committed outside of Transactionsyes infoisolated transactions for atomic changes and binary logging for safe writes
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoThe original contents of fields are not stored in the Manticore index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnoyes, based on authentication and database rulesAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no

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More resources
etcdFirebase Realtime DatabaseGoogle Cloud DatastoreManticore Search
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