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DBMS > Bangdb vs. Microsoft Azure Data Explorer vs. mSQL vs. NCache vs. Solr

System Properties Comparison Bangdb vs. Microsoft Azure Data Explorer vs. mSQL vs. NCache vs. Solr

Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonNCache  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphFully managed big data interactive analytics platformmSQL (Mini SQL) is a simple and lightweight RDBMSOpen-Source and Enterprise in-memory Key-Value StoreA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Relational DBMS infocolumn orientedRelational DBMSKey-value storeSearch engine
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
Document store
Search engine infoUsing distributed Lucene
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#347  Overall
#47  Document stores
#34  Graph DBMS
#31  Time Series DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score1.27
Rank#167  Overall
#77  Relational DBMS
Score0.94
Rank#195  Overall
#29  Key-value stores
Score42.91
Rank#24  Overall
#3  Search engines
Websitebangdb.comazure.microsoft.com/­services/­data-explorerhughestech.com.au/­products/­msqlwww.alachisoft.com/­ncachesolr.apache.org
Technical documentationdocs.bangdb.comdocs.microsoft.com/­en-us/­azure/­data-explorerwww.alachisoft.com/­resources/­docssolr.apache.org/­resources.html
DeveloperSachin Sinha, BangDBMicrosoftHughes TechnologiesAlachisoftApache Software Foundation
Initial release20122019199420052006
Current releaseBangDB 2.0, October 2021cloud service with continuous releases4.4, October 20215.3.3, April 20249.6.0, April 2024
License infoCommercial or Open SourceOpen Source infoBSD 3commercialcommercial infofree licenses can be providedOpen Source infoEnterprise Edition availableOpen Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++CC#, .NET, .NET Core, JavaJava
Server operating systemsLinuxhostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
Linux
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeFixed schema with schema-less datatypes (dynamic)yesschema-freeyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyespartial infoSupported data types are Lists, Queues, Hashsets, Dictionary and Counteryes infosupports customizable data types and automatic typing
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.noyesnonoyes
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialall fields are automatically indexedyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL like support with command line toolKusto Query Language (KQL), SQL subsetA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersSQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.Solr Parallel SQL Interface
APIs and other access methodsProprietary protocol
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
IDistributedCache
JCache
LINQ
Proprietary native API
Java API
RESTful HTTP/JSON API
Supported programming languagesC
C#
C++
Java
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Delphi
Java
Perl
PHP
Tcl
.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, Rnono infosupport for stored procedures with SQL-Server CLRJava plugins
Triggersyes, Notifications (with Streaming only)yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes infoNotificationsyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmSharding infoImplicit feature of the cloud servicenoneyesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneyes, with selectable consistency levelyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyEventual Consistency
Immediate Consistency
noneEventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology
Eventual Consistency
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnonooptimistic locking and pessimistic lockingoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesnoyesyes
Durability infoSupport for making data persistentyes, implements WAL (Write ahead log) as wellyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes, run db with in-memory only modenonoyesyes
User concepts infoAccess controlyes (enterprise version only)Azure Active Directory AuthenticationnoAuthentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)yes
More information provided by the system vendor
BangdbMicrosoft Azure Data ExplorermSQL infoMini SQLNCacheSolr
Specific characteristicsNCache has been the market leader in .NET Distributed Caching since 2005 . NCache...
» more
Competitive advantagesNCache is 100% .NET/ .NET Core based which fully supports ASP.NET Core Sessions ,...
» more
Typical application scenariosNCache enables industries like retail, finance, banking IoT, travel, ecommerce, healthcare...
» more
Key customersBank of America, Citi, Natures Way, Charter Spectrum, Barclays, Henry Schein, GBM,...
» more
Market metricsMarket Leader in .NET Distributed Caching since 2005.
» more
Licensing and pricing modelsNCache Open Source is free on an as-is basis without any support. NCache Enterprise...
» more

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More resources
BangdbMicrosoft Azure Data ExplorermSQL infoMini SQLNCacheSolr
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