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DBMS > Firebase Realtime Database vs. Microsoft Azure Data Explorer vs. Tarantool vs. Tkrzw vs. Yanza

System Properties Comparison Firebase Realtime Database vs. Microsoft Azure Data Explorer vs. Tarantool vs. Tkrzw vs. Yanza

Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTarantool  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionCloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.Fully managed big data interactive analytics platformIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto CabinetTime Series DBMS for IoT Applications
Primary database modelDocument storeRelational DBMS infocolumn orientedDocument store
Key-value store
Relational DBMS
Key-value storeTime Series DBMS
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Spatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score14.29
Rank#39  Overall
#6  Document stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitefirebase.google.com/­products/­realtime-databaseazure.microsoft.com/­services/­data-explorerwww.tarantool.iodbmx.net/­tkrzwyanza.com
Technical documentationfirebase.google.com/­docs/­databasedocs.microsoft.com/­en-us/­azure/­data-explorerwww.tarantool.io/­en/­doc
DeveloperGoogle infoacquired by Google 2014MicrosoftVKMikio HirabayashiYanza
Initial release20122019200820202015
Current releasecloud service with continuous releases2.10.0, May 20220.9.3, August 2020
License infoCommercial or Open SourcecommercialcommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool EnterpriseOpen Source infoApache Version 2.0commercial infofree version available
Cloud-based only infoOnly available as a cloud serviceyesyesnonono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC and C++C++
Server operating systemshostedhostedBSD
Linux
macOS
Linux
macOS
Windows
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)Flexible data schema: relational definition for tables with ability to store json-like documents in columnsschema-freeschema-free
Typing infopredefined data types such as float or dateyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesstring, double, decimal, uuid, integer, blob, boolean, datetimenono
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.noyesnonono
Secondary indexesyesall fields are automatically indexedyesno
SQL infoSupport of SQLnoKusto Query Language (KQL), SQL subsetFull-featured ANSI SQL supportnono
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Open binary protocolHTTP API
Supported programming languagesJava
JavaScript
Objective-C
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
C++
Java
Python
Ruby
any language that supports HTTP calls
Server-side scripts infoStored procedureslimited functionality with using 'rules'Yes, possible languages: KQL, Python, RLua, C and SQL stored proceduresnono
TriggersCallbacks are triggered when data changesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes, before/after data modification events, on replication events, client session eventsnoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.nonenone
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Asynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
nonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Eventual Consistency
Immediate Consistency
Casual consistency across sharding partitions
Eventual consistency within replicaset partition infowhen using asyncronous replication
Immediate Consistency within single instance
Sequential consistency including linearizable read within replicaset partition infowhen using Raft
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyesyes, cooperative multitaskingyesyes
Durability infoSupport for making data persistentyesyesyes, write ahead loggingyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes, full featured in-memory storage engine with persistenceyes infousing specific database classes
User concepts infoAccess controlyes, based on authentication and database rulesAzure Active Directory AuthenticationAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
nono

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More resources
Firebase Realtime DatabaseMicrosoft Azure Data ExplorerTarantoolTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetYanza
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