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DBMS > Bangdb vs. Hazelcast vs. Heroic vs. Microsoft Azure Data Explorer vs. NCache

System Properties Comparison Bangdb vs. Hazelcast vs. Heroic vs. Microsoft Azure Data Explorer vs. NCache

Editorial information provided by DB-Engines
NameBangdb  Xexclude from comparisonHazelcast  Xexclude from comparisonHeroic  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNCache  Xexclude from comparison
DescriptionConverged and high performance database for device data, events, time series, document and graphA widely adopted in-memory data gridTime Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearchFully managed big data interactive analytics platformOpen-Source and Enterprise in-memory Key-Value Store
Primary database modelDocument store
Graph DBMS
Time Series DBMS
Key-value storeTime Series DBMSRelational DBMS infocolumn orientedKey-value store
Secondary database modelsSpatial DBMSDocument store infoJSON support with IMDG 3.12Document 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.16
Rank#338  Overall
#47  Document stores
#32  Graph DBMS
#31  Time Series DBMS
Score5.46
Rank#61  Overall
#7  Key-value stores
Score0.46
Rank#265  Overall
#22  Time Series DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.96
Rank#195  Overall
#29  Key-value stores
Websitebangdb.comhazelcast.comgithub.com/­spotify/­heroicazure.microsoft.com/­services/­data-explorerwww.alachisoft.com/­ncache
Technical documentationdocs.bangdb.comhazelcast.org/­imdg/­docsspotify.github.io/­heroicdocs.microsoft.com/­en-us/­azure/­data-explorerwww.alachisoft.com/­resources/­docs
DeveloperSachin Sinha, BangDBHazelcastSpotifyMicrosoftAlachisoft
Initial release20122008201420192005
Current releaseBangDB 2.0, October 20215.3.6, November 2023cloud service with continuous releases5.3.3, April 2024
License infoCommercial or Open SourceOpen Source infoBSD 3Open Source infoApache Version 2; commercial licenses availableOpen Source infoApache 2.0commercialOpen Source infoEnterprise Edition available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++JavaJavaC#, .NET, .NET Core, Java
Server operating systemsLinuxAll OS with a Java VMhostedLinux
Windows
Data schemeschema-freeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyes: string, long, double, int, geospatial, stream, eventsyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typespartial infoSupported data types are Lists, Queues, Hashsets, Dictionary and Counter
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.noyes infothe object must implement a serialization strategynoyesno
Secondary indexesyes infosecondary, composite, nested, reverse, geospatialyesyes infovia Elasticsearchall fields are automatically indexedyes
SQL infoSupport of SQLSQL like support with command line toolSQL-like query languagenoKusto Query Language (KQL), SQL subsetSQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.
APIs and other access methodsProprietary protocol
RESTful HTTP API
JCache
JPA
Memcached protocol
RESTful HTTP API
HQL (Heroic Query Language, a JSON-based language)
HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
IDistributedCache
JCache
LINQ
Proprietary native API
Supported programming languagesC
C#
C++
Java
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor ServicesnoYes, possible languages: KQL, Python, Rno infosupport for stored procedures with SQL-Server CLR
Triggersyes, Notifications (with Streaming only)yes infoEventsnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoNotifications
Partitioning methods infoMethods for storing different data on different nodesSharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithmShardingShardingSharding infoImplicit feature of the cloud serviceyes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factor, Knob for CAP (enterprise version only)yes infoReplicated Mapyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, with selectable consistency level
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemTunable consistency, set CAP knob accordinglyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology
Foreign keys infoReferential integritynonononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDone or two-phase-commit; repeatable reads; read commitednonooptimistic locking and pessimistic locking
Concurrency infoSupport for concurrent manipulation of datayes, optimistic concurrency controlyesyesyesyes
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 modeyesnonoyes
User concepts infoAccess controlyes (enterprise version only)Role-based access controlAzure Active Directory AuthenticationAuthentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)
More information provided by the system vendor
BangdbHazelcastHeroicMicrosoft Azure Data ExplorerNCache
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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BangdbHazelcastHeroicMicrosoft Azure Data ExplorerNCache
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