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DBMS > EsgynDB vs. Firebase Realtime Database vs. Microsoft Azure Data Explorer vs. ObjectBox vs. Tarantool

System Properties Comparison EsgynDB vs. Firebase Realtime Database vs. Microsoft Azure Data Explorer vs. ObjectBox vs. Tarantool

Editorial information provided by DB-Engines
NameEsgynDB  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonObjectBox  Xexclude from comparisonTarantool  Xexclude from comparison
DescriptionEnterprise-class SQL-on-Hadoop solution, powered by Apache TrafodionCloud-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 platformExtremely fast embedded database for small devices, IoT and MobileIn-memory computing platform with a flexible data schema for efficiently building high-performance applications
Primary database modelRelational DBMSDocument storeRelational DBMS infocolumn orientedObject oriented DBMSDocument store
Key-value store
Relational 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
Time Series DBMSSpatial DBMS infowith Tarantool/GIS extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#329  Overall
#146  Relational DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score1.72
Rank#144  Overall
#25  Document stores
#25  Key-value stores
#66  Relational DBMS
Websitewww.esgyn.cnfirebase.google.com/­products/­realtime-databaseazure.microsoft.com/­services/­data-explorerobjectbox.iowww.tarantool.io
Technical documentationfirebase.google.com/­docs/­databasedocs.microsoft.com/­en-us/­azure/­data-explorerdocs.objectbox.iowww.tarantool.io/­en/­doc
DeveloperEsgynGoogle infoacquired by Google 2014MicrosoftObjectBox LimitedVK
Initial release20152012201920172008
Current releasecloud service with continuous releases2.10.0, May 2022
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache License 2.0Open Source infoBSD-2, source-available extensions (modules), commercial licenses for Tarantool Enterprise
Cloud-based only infoOnly available as a cloud servicenoyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++, JavaC and C++C and C++
Server operating systemsLinuxhostedhostedAndroid
iOS
Linux
macOS
Windows
BSD
Linux
macOS
Data schemeyesschema-freeFixed schema with schema-less datatypes (dynamic)yesFlexible data schema: relational definition for tables with ability to store json-like documents in columns
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesstring, double, decimal, uuid, integer, blob, boolean, datetime
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 indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLyesnoKusto Query Language (KQL), SQL subsetnoFull-featured ANSI SQL support
APIs and other access methodsADO.NET
JDBC
ODBC
Android
iOS
JavaScript API
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Proprietary native APIOpen binary protocol
Supported programming languagesAll languages supporting JDBC/ODBC/ADO.NetJava
JavaScript
Objective-C
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
C
C#
C++
Erlang
Go
Java
JavaScript
Lua
Perl
PHP
Python
Rust
Server-side scripts infoStored proceduresJava Stored Procedureslimited functionality with using 'rules'Yes, possible languages: KQL, Python, RnoLua, C and SQL stored procedures
TriggersnoCallbacks are triggered when data changesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes, before/after data modification events, on replication events, client session events
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud servicenoneSharding, partitioned with virtual buckets by user defined affinity key. Live resharding for scale up and scale down without maintenance downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication between multi datacentersyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.online/offline synchronization between client and serverAsynchronous replication with multi-master option
Configurable replication topology (full-mesh, chain, star)
Synchronous quorum replication (with Raft)
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Eventual Consistency
Immediate Consistency
Immediate ConsistencyCasual 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
Foreign keys infoReferential integrityyesnonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesnoACIDACID, with serializable isolation and linearizable read (within partition); Configurable MVCC (within partition); No cross-shard distributed transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, cooperative multitasking
Durability infoSupport for making data persistentyesyesyesyesyes, write ahead logging
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes, full featured in-memory storage engine with persistence
User concepts infoAccess controlfine grained access rights according to SQL-standardyes, based on authentication and database rulesAzure Active Directory AuthenticationyesAccess Control Lists
Mutual TLS authentication for Tarantol Enterprise
Password based authentication
Role-based access control (RBAC) and LDAP for Tarantol Enterprise
Users and Roles
More information provided by the system vendor
EsgynDBFirebase Realtime DatabaseMicrosoft Azure Data ExplorerObjectBoxTarantool
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More resources
EsgynDBFirebase Realtime DatabaseMicrosoft Azure Data ExplorerObjectBoxTarantool
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