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DBMS > Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer vs. NCache vs. Tigris

System Properties Comparison Hazelcast vs. Ingres vs. Microsoft Azure Data Explorer vs. NCache vs. Tigris

Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonIngres  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNCache  Xexclude from comparisonTigris  Xexclude from comparison
DescriptionA widely adopted in-memory data gridWell established RDBMSFully managed big data interactive analytics platformOpen-Source and Enterprise in-memory Key-Value StoreA horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelKey-value storeRelational DBMSRelational DBMS infocolumn orientedKey-value storeDocument store
Key-value store
Search engine
Time Series DBMS
Secondary database modelsDocument 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
Score5.46
Rank#61  Overall
#7  Key-value stores
Score3.80
Rank#82  Overall
#44  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.96
Rank#195  Overall
#29  Key-value stores
Score0.09
Rank#363  Overall
#49  Document stores
#54  Key-value stores
#22  Search engines
#38  Time Series DBMS
Websitehazelcast.comwww.actian.com/­databases/­ingresazure.microsoft.com/­services/­data-explorerwww.alachisoft.com/­ncachewww.tigrisdata.com
Technical documentationhazelcast.org/­imdg/­docsdocs.actian.com/­ingresdocs.microsoft.com/­en-us/­azure/­data-explorerwww.alachisoft.com/­resources/­docswww.tigrisdata.com/­docs
DeveloperHazelcastActian CorporationMicrosoftAlachisoftTigris Data, Inc.
Initial release20081974 infooriginally developed at University Berkely in early 1970s201920052022
Current release5.3.6, November 202311.2, May 2022cloud service with continuous releases5.3.3, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availablecommercialcommercialOpen Source infoEnterprise Edition availableOpen Source infoApache Version 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCC#, .NET, .NET Core, Java
Server operating systemsAll OS with a Java VMAIX
HP Open VMS
HP-UX
Linux
Solaris
Windows
hostedLinux
Windows
Linux
macOS
Windows
Data schemeschema-freeyesFixed schema with schema-less datatypes (dynamic)schema-freeyes
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-typespartial infoSupported data types are Lists, Queues, Hashsets, Dictionary and Counteryes
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.yes infothe object must implement a serialization strategyno infobut tools for importing/exporting data from/to XML-files availableyesnono
Secondary indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLSQL-like query languageyesKusto Query Language (KQL), SQL subsetSQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.no
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
IDistributedCache
JCache
LINQ
Proprietary native API
CLI Client
gRPC
RESTful HTTP API
Supported programming languages.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
Go
Java
JavaScript (Node.js)
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor ServicesyesYes, possible languages: KQL, Python, Rno infosupport for stored procedures with SQL-Server CLRno
Triggersyes infoEventsyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoNotificationsno
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning infoIngres Star to access multiple databases simultaneouslySharding infoImplicit feature of the cloud serviceyesSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated MapIngres Replicatoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, with selectable consistency levelyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology
Immediate Consistency
Foreign keys infoReferential integritynoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitedACIDnooptimistic locking and pessimistic lockingACID
Concurrency infoSupport for concurrent manipulation of datayesyes infoMVCCyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes, using FoundationDB
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlRole-based access controlfine grained access rights according to SQL-standardAzure Active Directory AuthenticationAuthentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)Access rights for users and roles
More information provided by the system vendor
HazelcastIngresMicrosoft Azure Data ExplorerNCacheTigris
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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HazelcastIngresMicrosoft Azure Data ExplorerNCacheTigris
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