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DBMS > AlaSQL vs. Faircom DB vs. Firebase Realtime Database vs. HEAVY.AI vs. Microsoft Azure Data Explorer

System Properties Comparison AlaSQL vs. Faircom DB vs. Firebase Realtime Database vs. HEAVY.AI vs. Microsoft Azure Data Explorer

Editorial information provided by DB-Engines
NameAlaSQL  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonFirebase Realtime Database  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionJavaScript DBMS libraryNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully managed big data interactive analytics platform
Primary database modelDocument store
Relational DBMS
Key-value store
Relational DBMS
Document storeRelational DBMSRelational DBMS infocolumn oriented
Secondary database modelsSpatial DBMSDocument 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.46
Rank#260  Overall
#40  Document stores
#121  Relational DBMS
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score14.29
Rank#39  Overall
#6  Document stores
Score1.77
Rank#141  Overall
#65  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Websitealasql.orgwww.faircom.com/­products/­faircom-dbfirebase.google.com/­products/­realtime-databasegithub.com/­heavyai/­heavydb
www.heavy.ai
azure.microsoft.com/­services/­data-explorer
Technical documentationgithub.com/­AlaSQL/­alasqldocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlfirebase.google.com/­docs/­databasedocs.heavy.aidocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperAndrey Gershun & Mathias R. WulffFairCom CorporationGoogle infoacquired by Google 2014HEAVY.AI, Inc.Microsoft
Initial release20141979201220162019
Current releaseV12, November 20205.10, January 2022cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoMIT-Licensecommercial infoRestricted, free version availablecommercialOpen Source infoApache Version 2; enterprise edition availablecommercial
Cloud-based only infoOnly available as a cloud servicenonoyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScriptANSI C, C++C++ and CUDA
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js)AIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
hostedLinuxhosted
Data schemeschema-freeschema free, schema optional, schema required, partial schema,schema-freeyesFixed schema with schema-less datatypes (dynamic)
Typing infopredefined data types such as float or datenoyes, ANSI SQL Types, JSON, typed binary structuresyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types
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.nonononoyes
Secondary indexesnoyesyesnoall fields are automatically indexed
SQL infoSupport of SQLClose to SQL99, but no user access control, stored procedures and host language bindings.yes, ANSI SQL with proprietary extensionsnoyesKusto Query Language (KQL), SQL subset
APIs and other access methodsJavaScript APIADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
Android
iOS
JavaScript API
RESTful HTTP API
JDBC
ODBC
Thrift
Vega
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesJavaScript.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
Java
JavaScript
Objective-C
All languages supporting JDBC/ODBC/Thrift
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++limited functionality with using 'rules'noYes, possible languages: KQL, Python, R
TriggersyesyesCallbacks are triggered when data changesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodesnoneFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningSharding infoRound robinSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Multi-source replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemnoneEventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Eventual Consistency infoif the client is offline
Immediate Consistency infoif the client is online
Immediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datayes infoonly for local storage and DOM-storagetunable from ACID to Eventually Consistentyesnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyes infoby using IndexedDB, SQL.JS or proprietary FileStorageYes, tunable from durable to delayed durability to in-memoryyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesyesno
User concepts infoAccess controlnoFine grained access rights according to SQL-standard with additional protections for filesyes, based on authentication and database rulesfine grained access rights according to SQL-standardAzure Active Directory Authentication

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More resources
AlaSQLFaircom DB infoformerly c-treeACEFirebase Realtime DatabaseHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft Azure Data Explorer
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