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DBMS > HEAVY.AI vs. Memgraph vs. Microsoft Azure Data Explorer vs. Microsoft Azure SQL Database vs. Weaviate

System Properties Comparison HEAVY.AI vs. Memgraph vs. Microsoft Azure Data Explorer vs. Microsoft Azure SQL Database vs. Weaviate

Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMemgraph  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonWeaviate  Xexclude from comparison
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareAn open source graph database built for real-time streaming and compatible with Neo4jFully managed big data interactive analytics platformDatabase as a Service offering with high compatibility to Microsoft SQL ServerAn AI-native realtime vector database engine that integrates scalable machine learning models.
Primary database modelRelational DBMSGraph DBMSRelational DBMS infocolumn orientedRelational DBMSVector DBMS
Secondary database modelsSpatial DBMSDocument 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
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score3.19
Rank#94  Overall
#8  Graph DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score76.78
Rank#16  Overall
#11  Relational DBMS
Score1.52
Rank#153  Overall
#5  Vector DBMS
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
memgraph.comazure.microsoft.com/­services/­data-explorerazure.microsoft.com/­en-us/­products/­azure-sql/­databasegithub.com/­weaviate/­weaviate
weaviate.io
Technical documentationdocs.heavy.aimemgraph.com/­docsdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.microsoft.com/­en-us/­azure/­azure-sqlweaviate.io/­developers/­weaviate
Social network pagesLinkedInTwitterFacebookGitHubDiscord
DeveloperHEAVY.AI, Inc.Memgraph LtdMicrosoftMicrosoftWeaviate B.V.
Initial release20162017201920102019
Current release5.10, January 2022cloud service with continuous releasesV121.19, May 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availableOpen Source infoBSL 1.1; commercial license for enterprise edition availablecommercialcommercialOpen Source infocommercial license available with Weaviate Enterprise
Cloud-based only infoOnly available as a cloud servicenonoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ and CUDAC and C++C++Go
Server operating systemsLinuxLinuxhostedhosted
Data schemeyesschema-free and schema-optionalFixed schema with schema-less datatypes (dynamic)yesyes, maps to GraphQL interface
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-typesyesyes infostring, int, float, geo point, date, cross reference, fuzzy references
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.nonoyesyesno
Secondary indexesnoall fields are automatically indexedyesyes infoall data objects are indexed in a semantic vector space (the Contextionary), all primitive fields are indexed
SQL infoSupport of SQLyesnoKusto Query Language (KQL), SQL subsetyesGraphQL is used as query language
APIs and other access methodsJDBC
ODBC
Thrift
Vega
Bolt protocol
Cypher query language
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
GraphQL query language
RESTful HTTP/JSON API
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaScript / TypeScript
Python
Server-side scripts infoStored proceduresnoYes, possible languages: KQL, Python, RTransact SQLno
Triggersnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinSharding infodynamic graph partitioningSharding infoImplicit feature of the cloud serviceSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationMulti-source replication using RAFTyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.yes, with always 3 replicas availableyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynoyes inforelationships in graphsnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infowith snapshot isolationnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyes, multi-version concurrency control (MVCC)yesyesyes
Durability infoSupport for making data persistentyesyes infowith periodic snapshot and write-ahead logging (WAL) of changesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardUsers, roles and permissionsAzure Active Directory Authenticationfine grained access rights according to SQL-standardAPI Keys
OpenID Connect Discovery
More information provided by the system vendor
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022MemgraphMicrosoft Azure Data ExplorerMicrosoft Azure SQL Database infoformerly SQL AzureWeaviate
Specific characteristicsMemgraph directly connects to your streaming infrastructure so you and your team...
» more
Weaviate is an open source vector database that is robust, scalable, cloud-native,...
» more
Competitive advantagesBusiness Source License ensures a future for the Memgraph community MAGE algorithm...
» more
Flexible deployment - Free, open source or fully-managed cloud vector database service...
» more
Typical application scenariosGraph algorithms in bioinformatics Social network analysis Cryptocurrency network...
» more
As a database supporting the development of generative AI and semantic search applications...
» more
Key customersAll companies that have data. ​
» more
Market metricsAs of mid 2023: Over 2 million open source downloads 3500+ Weaviate Slack community...
» more
Licensing and pricing modelsYou can check out our pricing model and licenses on the company website .
» more
Weaviate is open-source, and free to use. Weaviate is also available as a fully managed...
» more

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More resources
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022MemgraphMicrosoft Azure Data ExplorerMicrosoft Azure SQL Database infoformerly SQL AzureWeaviate
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