DB-EnginesExtremeDB: mitigate connectivity issues in a DBMSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > InfinityDB vs. Kinetica vs. Microsoft Azure Data Explorer vs. SwayDB

System Properties Comparison InfinityDB vs. Kinetica vs. Microsoft Azure Data Explorer vs. SwayDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameInfinityDB  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSwayDB  Xexclude from comparison
DescriptionA Java embedded Key-Value Store which extends the Java Map interfaceFully vectorized database across both GPUs and CPUsFully managed big data interactive analytics platformAn embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage
Primary database modelKey-value storeRelational DBMSRelational DBMS infocolumn orientedKey-value store
Secondary database modelsSpatial DBMS
Time Series DBMS
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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.08
Rank#365  Overall
#55  Key-value stores
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.04
Rank#387  Overall
#61  Key-value stores
Websiteboilerbay.comwww.kinetica.comazure.microsoft.com/­services/­data-explorerswaydb.simer.au
Technical documentationboilerbay.com/­infinitydb/­manualdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperBoiler Bay Inc.KineticaMicrosoftSimer Plaha
Initial release2002201220192018
Current release4.07.1, August 2021cloud service with continuous releases
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoGNU Affero GPL V3.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++Scala
Server operating systemsAll OS with a Java VMLinuxhosted
Data schemeyes infonested virtual Java Maps, multi-value, logical ‘tuple space’ runtime Schema upgradeyesFixed schema with schema-less datatypes (dynamic)schema-free
Typing infopredefined data types such as float or dateyes infoall Java primitives, Date, CLOB, BLOB, huge sparse arraysyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesno
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.nonoyesno
Secondary indexesno infomanual creation possible, using inversions based on multi-value capabilityyesall fields are automatically indexedno
SQL infoSupport of SQLnoSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetno
APIs and other access methodsAccess via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/­docs/­ItemSpaceDataStructures.htm)
JDBC
ODBC
RESTful HTTP API
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
Supported programming languagesJavaC++
Java
JavaScript (Node.js)
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Java
Kotlin
Scala
Server-side scripts infoStored proceduresnouser defined functionsYes, possible languages: KQL, Python, Rno
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoImplicit feature of the cloud servicenone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency infoREAD-COMMITTED or SERIALIZEDImmediate Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integrityno infomanual creation possible, using inversions based on multi-value capabilityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoOptimistic locking for transactions; no isolation for bulk loadsnonoAtomic execution of operations
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlnoAccess rights for users and roles on table levelAzure Active Directory Authenticationno

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
InfinityDBKineticaMicrosoft Azure Data ExplorerSwayDB
Recent citations in the news

Kinetica Delivers Real-Time Vector Similarity Search
21 March 2024, insideBIGDATA

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data
18 March 2024, SiliconANGLE News

Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise
18 March 2024, GlobeNewswire

Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

Transforming spatiotemporal data analysis with GPUs and generative AI
30 October 2023, InfoWorld

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, azure.microsoft.com

Update records in a Kusto Database (public preview) | Azure updates
20 February 2024, azure.microsoft.com

Public Preview: Azure Data Explorer connector for Apache Flink | Azure updates
8 January 2024, azure.microsoft.com

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

New Features for graph-match KQL Operator: Enhanced Pattern Matching and Cycle Control | Azure updates
24 January 2024, azure.microsoft.com

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