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DBMS > Apache Impala vs. IBM Db2 vs. jBASE vs. Microsoft Azure Data Explorer vs. NCache

System Properties Comparison Apache Impala vs. IBM Db2 vs. jBASE vs. Microsoft Azure Data Explorer vs. NCache

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonIBM Db2 infoformerly named DB2 or IBM Database 2  Xexclude from comparisonjBASE  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonNCache  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopCommon in IBM host environments, 2 different versions for host and Windows/LinuxA robust multi-value DBMS comprising development tools and middlewareFully managed big data interactive analytics platformOpen-Source and Enterprise in-memory Key-Value Store
Primary database modelRelational DBMSRelational DBMS infoSince Version 10.5 support for JSON/BSON documents compatible with MongoDBMultivalue DBMSRelational DBMS infocolumn orientedKey-value store
Secondary database modelsDocument storeDocument store
RDF store infoin Db2 LUW (Linux, Unix, Windows)
Spatial DBMS infowith Db2 Spatial Extender
Document 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
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score128.46
Rank#8  Overall
#5  Relational DBMS
Score1.41
Rank#159  Overall
#3  Multivalue DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.94
Rank#195  Overall
#29  Key-value stores
Websiteimpala.apache.orgwww.ibm.com/­products/­db2www.rocketsoftware.com/­products/­rocket-multivalue-application-development-platform/­rocket-jbaseazure.microsoft.com/­services/­data-explorerwww.alachisoft.com/­ncache
Technical documentationimpala.apache.org/­impala-docs.htmlwww.ibm.com/­docs/­en/­db2docs.rocketsoftware.com/­bundle?labelkey=jbase_5.9docs.microsoft.com/­en-us/­azure/­data-explorerwww.alachisoft.com/­resources/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaIBMRocket Software (formerly Zumasys)MicrosoftAlachisoft
Initial release20131983 infohost version199120192005
Current release4.1.0, June 202212.1, October 20165.7cloud service with continuous releases5.3.3, April 2024
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infofree version is availablecommercialcommercialOpen Source infoEnterprise Edition available
Cloud-based only infoOnly available as a cloud servicenononoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C and C++C#, .NET, .NET Core, Java
Server operating systemsLinuxAIX
HP-UX
Linux
Solaris
Windows
z/OS
AIX
Linux
Windows
hostedLinux
Windows
Data schemeyesyesschema-freeFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyesyesoptionalyes 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.noyesyesno
Secondary indexesyesyesall fields are automatically indexedyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesEmbedded SQL for jBASE in BASICKusto 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 methodsJDBC
ODBC
ADO.NET
JDBC
JSON style queries infoMongoDB compatible
ODBC
XQuery
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
IDistributedCache
JCache
LINQ
Proprietary native API
Supported programming languagesAll languages supporting JDBC/ODBCC
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic
.Net
Basic
Jabbascript
Java
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesyesYes, possible languages: KQL, Python, Rno infosupport for stored procedures with SQL-Server CLR
Triggersnoyesyesyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyes infoNotifications
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoonly with Windows/Unix/Linux VersionShardingSharding infoImplicit feature of the cloud serviceyes
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryes infowith separate tools (MQ, InfoSphere)yesyes 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 methodsyes infoquery execution via MapReducenonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology
Foreign keys infoReferential integritynoyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnooptimistic locking and pessimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardAccess rights can be defined down to the item levelAzure Active Directory AuthenticationAuthentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)
More information provided by the system vendor
Apache ImpalaIBM Db2 infoformerly named DB2 or IBM Database 2jBASEMicrosoft 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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Apache ImpalaIBM Db2 infoformerly named DB2 or IBM Database 2jBASEMicrosoft Azure Data ExplorerNCache
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