DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Apache Jena - TDB vs. Ignite vs. Microsoft Azure Data Explorer vs. SiriDB vs. Yaacomo

System Properties Comparison Apache Jena - TDB vs. Ignite vs. Microsoft Azure Data Explorer vs. SiriDB vs. Yaacomo

Editorial information provided by DB-Engines
NameApache Jena - TDB  Xexclude from comparisonIgnite  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSiriDB  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionA RDF storage and query DBMS, shipped as an optional-use component of the Apache Jena frameworkApache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.Fully managed big data interactive analytics platformOpen Source Time Series DBMSOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRDF storeKey-value store
Relational DBMS
Relational DBMS infocolumn orientedTime Series DBMSRelational DBMS
Secondary database modelsDocument 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
Score3.62
Rank#83  Overall
#3  RDF stores
Score3.11
Rank#96  Overall
#15  Key-value stores
#49  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.07
Rank#378  Overall
#42  Time Series DBMS
Websitejena.apache.org/­documentation/­tdb/­index.htmlignite.apache.orgazure.microsoft.com/­services/­data-explorersiridb.comyaacomo.com
Technical documentationjena.apache.org/­documentation/­tdb/­index.htmlapacheignite.readme.io/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.siridb.com
DeveloperApache Software Foundation infooriginally developed by HP LabsApache Software FoundationMicrosoftCesbitQ2WEB GmbH
Initial release20002015201920172009
Current release4.9.0, July 2023Apache Ignite 2.6cloud service with continuous releases
License infoCommercial or Open SourceOpen Source infoApache License, Version 2.0Open Source infoApache 2.0commercialOpen Source infoMIT Licensecommercial
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 languageJavaC++, Java, .NetC
Server operating systemsAll OS with a Java VMLinux
OS X
Solaris
Windows
hostedLinuxAndroid
Linux
Windows
Data schemeyes infoRDF SchemasyesFixed schema with schema-less datatypes (dynamic)yesyes
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-typesyes infoNumeric datayes
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.yesyesnono
Secondary indexesyesyesall fields are automatically indexedyesyes
SQL infoSupport of SQLnoANSI-99 for query and DML statements, subset of DDLKusto Query Language (KQL), SQL subsetnoyes
APIs and other access methodsFuseki infoREST-style SPARQL HTTP Interface
Jena RDF API
RIO infoRDF Input/Output
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
HTTP APIJDBC
ODBC
Supported programming languagesJavaC#
C++
Java
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
Server-side scripts infoStored proceduresyesyes (compute grid and cache interceptors can be used instead)Yes, possible languages: KQL, Python, Rno
Triggersyes infovia event handleryes (cache interceptors and events)yes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicynoyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoImplicit feature of the cloud serviceShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes (replicated cache)yes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yesSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes (compute grid and hadoop accelerator)Spark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoTDB TransactionsACIDnonoACID
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.yesnoyesyes
User concepts infoAccess controlAccess control via Jena SecuritySecurity Hooks for custom implementationsAzure Active Directory Authenticationsimple rights management via user accountsfine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Apache Jena - TDBIgniteMicrosoft Azure Data ExplorerSiriDBYaacomo
Recent citations in the news

Sparql Secrets In Jena-Fuseki - DataScienceCentral.com
24 July 2022, Data Science Central

Extract and query knowledge graphs using Apache Jena (SPARQL Engine)
4 December 2019, Towards Data Science

6 Java Libraries for Machine Learning – AIM
3 October 2023, Analytics India Magazine

A catalogue with semantic annotations makes multilabel datasets FAIR | Scientific Reports
4 May 2022, Nature.com

MarkLogic Hones Its Triple Store
18 August 2015, Datanami

provided by Google News

GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024
8 February 2024, PR Newswire

GridGain Showcases Power of Apache Ignite at Community Over Code Conference
5 October 2023, Datanami

Apache Ignite: Distributed Database
18 August 2015, ignite.apache.org

Apache Ignite: An Overview
6 September 2023, Open Source For You

What is Apache Ignite? How is Apache Ignite Used?
18 July 2022, The Stack

provided by Google News

We’re retiring Azure Time Series Insights on 7 July 2024 – transition to Azure Data Explorer | Azure updates
31 May 2024, Microsoft

Update records in a Kusto Database (public preview) | Azure updates
20 February 2024, Microsoft

Public Preview: Azure Data Explorer connector for Apache Flink | Azure updates
8 January 2024, Microsoft

Announcing General Availability to migrate Virtual Network injected Azure Data Explorer Cluster to Private Endpoints ...
5 February 2024, Microsoft

Migration of Azure Virtual Network injected Azure Data Explorer cluster to Private Endpoints | Azure updates
4 December 2023, Microsoft

provided by Google News



Share this page

Featured Products

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Present your product here