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

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

Editorial information provided by DB-Engines
NameFirebase Realtime Database  Xexclude from comparisonIRONdb  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonTarantool  Xexclude from comparisonYanza  Xexclude from comparison
IRONdb seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.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.A distributed Time Series DBMS with a focus on scalability, fault tolerance and operational simplicityFully managed big data interactive analytics platformIn-memory computing platform with a flexible data schema for efficiently building high-performance applicationsTime Series DBMS for IoT Applications
Primary database modelDocument storeTime Series DBMSRelational DBMS infocolumn orientedDocument store
Key-value store
Relational DBMS
Time 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
Websitefirebase.google.com/­products/­realtime-databasewww.circonus.com/solutions/time-series-database/azure.microsoft.com/­services/­data-explorerwww.tarantool.ioyanza.com
Technical documentationfirebase.google.com/­docs/­databasedocs.circonus.com/irondb/category/getting-starteddocs.microsoft.com/­en-us/­azure/­data-explorerwww.tarantool.io/­en/­doc
DeveloperGoogle infoacquired by Google 2014Circonus LLC.MicrosoftVKYanza
Initial release20122017201920082015
Current releaseV0.10.20, January 2018cloud service with continuous releases2.10.0, May 2022
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprisecommercial infofree version available
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono 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 and C++
Server operating systemshostedLinuxhostedBSD
Linux
macOS
Windows
Data schemeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)Flexible data schema: relational definition for tables with ability to store json-like documents in columnsschema-free
Typing infopredefined data types such as float or dateyesyes infotext, numeric, histogramsyes 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, datetimeno
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.nonoyesnono
Secondary indexesyesnoall fields are automatically indexedyesno
SQL infoSupport of SQLnoSQL-like query language (Circonus Analytics Query Language: CAQL)Kusto Query Language (KQL), SQL subsetFull-featured ANSI SQL supportno
APIs and other access methodsAndroid
iOS
JavaScript API
RESTful HTTP API
HTTP APIMicrosoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Open binary protocolHTTP API
Supported programming languagesJava
JavaScript
Objective-C
.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Lua
Perl
PHP
Python
R
Ruby
Rust
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
any language that supports HTTP calls
Server-side scripts infoStored procedureslimited functionality with using 'rules'yes, in LuaYes, possible languages: KQL, Python, RLua, C and SQL stored proceduresno
TriggersCallbacks are triggered when data changesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes, before/after data modification events, on replication events, client session eventsyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesAutomatic, metric affinity per nodeSharding 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.none
Replication methods infoMethods for redundantly storing data on multiple nodesconfigurable replication factor, datacenter awareyes 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)
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate consistency per node, eventual consistency across nodesEventual 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 Consistency
Foreign keys infoReferential integritynononoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayesnonoACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactionsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, cooperative multitaskingyes
Durability infoSupport for making data persistentyesyesyesyes, write ahead loggingyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlyes, based on authentication and database rulesnoAzure 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
no

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More resources
Firebase Realtime DatabaseIRONdbMicrosoft Azure Data ExplorerTarantoolYanza
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