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DBMS > etcd vs. Google Cloud Firestore vs. Hazelcast vs. Microsoft Azure Synapse Analytics vs. Tkrzw

System Properties Comparison etcd vs. Google Cloud Firestore vs. Hazelcast vs. Microsoft Azure Synapse Analytics vs. Tkrzw

Editorial information provided by DB-Engines
Nameetcd  Xexclude from comparisonGoogle Cloud Firestore  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparison
DescriptionA distributed reliable key-value storeCloud 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 gridElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerA 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 modelKey-value storeDocument storeKey-value storeRelational DBMSKey-value store
Secondary database modelsDocument store infoJSON support with IMDG 3.12
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.03
Rank#54  Overall
#5  Key-value stores
Score7.36
Rank#53  Overall
#9  Document stores
Score5.46
Rank#61  Overall
#7  Key-value stores
Score19.93
Rank#31  Overall
#19  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Websiteetcd.io
github.com/­etcd-io/­etcd
firebase.google.com/­products/­firestorehazelcast.comazure.microsoft.com/­services/­synapse-analyticsdbmx.net/­tkrzw
Technical documentationetcd.io/­docs
github.com/­etcd-io/­etcd/­tree/­master/­Documentation
firebase.google.com/­docs/­firestorehazelcast.org/­imdg/­docsdocs.microsoft.com/­azure/­synapse-analytics
DeveloperGoogleHazelcastMicrosoftMikio Hirabayashi
Initial release2017200820162020
Current release3.4, August 20195.3.6, November 20230.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen Source infoApache Version 2; commercial licenses availablecommercialOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageGoJavaC++C++
Server operating systemsFreeBSD
Linux
Windows infoexperimental
hostedAll OS with a Java VMhostedLinux
macOS
Data schemeschema-freeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or datenoyesyesyesno
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 infothe object must implement a serialization strategynono
Secondary indexesnoyesyesyes
SQL infoSupport of SQLnonoSQL-like query languageyesno
APIs and other access methodsgRPC
JSON over HTTP
Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
ADO.NET
JDBC
ODBC
Supported programming languages.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl
Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C#
Java
PHP
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnoyes, Firebase Rules & Cloud Functionsyes infoEvent Listeners, Executor ServicesTransact SQLno
Triggersyes, watching key changesyes, with Cloud Functionsyes infoEventsnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding, horizontal partitioningnone
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 replicationyes infoReplicated Mapyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoUsing Cloud Dataflowyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononono infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesone or two-phase-commit; repeatable reads; read commitedACID
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.noyesyes infousing specific database classes
User concepts infoAccess controlnoAccess 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 controlyesno

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More resources
etcdGoogle Cloud FirestoreHazelcastMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet
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