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

DBMS > Amazon DynamoDB vs. Amazon Neptune vs. HEAVY.AI vs. Microsoft Azure Data Explorer vs. Sadas Engine

System Properties Comparison Amazon DynamoDB vs. Amazon Neptune vs. HEAVY.AI vs. Microsoft Azure Data Explorer vs. Sadas Engine

Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonAmazon Neptune  Xexclude from comparisonHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonSadas Engine  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudFast, reliable graph database built for the cloudA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareFully managed big data interactive analytics platformSADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments
Primary database modelDocument store
Key-value store
Graph DBMS
RDF store
Relational DBMSRelational DBMS infocolumn orientedRelational 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score74.45
Rank#17  Overall
#3  Document stores
#2  Key-value stores
Score2.29
Rank#113  Overall
#9  Graph DBMS
#5  RDF stores
Score1.64
Rank#145  Overall
#67  Relational DBMS
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.07
Rank#373  Overall
#157  Relational DBMS
Websiteaws.amazon.com/­dynamodbaws.amazon.com/­neptunegithub.com/­heavyai/­heavydb
www.heavy.ai
azure.microsoft.com/­services/­data-explorerwww.sadasengine.com
Technical documentationdocs.aws.amazon.com/­dynamodbaws.amazon.com/­neptune/­developer-resourcesdocs.heavy.aidocs.microsoft.com/­en-us/­azure/­data-explorerwww.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
DeveloperAmazonAmazonHEAVY.AI, Inc.MicrosoftSADAS s.r.l.
Initial release20122017201620192006
Current release5.10, January 2022cloud service with continuous releases8.0
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationscommercialOpen Source infoApache Version 2; enterprise edition availablecommercialcommercial infofree trial version available
Cloud-based only infoOnly available as a cloud serviceyesyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ and CUDAC++
Server operating systemshostedhostedLinuxhostedAIX
Linux
Windows
Data schemeschema-freeschema-freeyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyes
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 indexesyesnonoall fields are automatically indexedyes
SQL infoSupport of SQLnonoyesKusto Query Language (KQL), SQL subsetyes
APIs and other access methodsRESTful HTTP APIOpenCypher
RDF 1.1 / SPARQL 1.1
TinkerPop Gremlin
JDBC
ODBC
Thrift
Vega
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
JDBC
ODBC
Proprietary protocol
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
C#
Go
Java
JavaScript
PHP
Python
Ruby
Scala
All languages supporting JDBC/ODBC/Thrift
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C#
C++
Groovy
Java
PHP
Python
Server-side scripts infoStored proceduresnononoYes, possible languages: KQL, Python, Rno
Triggersyes infoby integration with AWS Lambdanonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoRound robinSharding infoImplicit feature of the cloud servicehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-availability zones high availability, asynchronous replication for up to 15 read replicas within a single region. Global database clusters consists of a primary write DB cluster in one region, and up to five secondary read DB clusters in different regions. Each secondary region can have up to 16 reader instances.Multi-source 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 methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonoSpark connector (open source): github.com/­Azure/­azure-kusto-sparkno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infoRelationships in graphsnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoACID across one or more tables within a single AWS account and regionACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyes infowith encyption-at-restyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infomanaged by 'Learn by Usage'
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)fine grained access rights according to SQL-standardAzure Active Directory AuthenticationAccess rights for users, groups and roles 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
3rd partiesCData: Connect to Big Data & NoSQL through standard Drivers.
» more

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

More resources
Amazon DynamoDBAmazon NeptuneHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft Azure Data ExplorerSadas Engine
DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

Increased popularity for consuming DBMS services out of the cloud
2 October 2015, Paul Andlinger

show all

Recent citations in the news

AWS announces Amazon DynamoDB zero-ETL integration with Amazon OpenSearch Service
28 November 2023, AWS Blog

Simplify cross-account access control with Amazon DynamoDB using resource-based policies | Amazon Web Services
20 March 2024, AWS Blog

Simplify private connectivity to Amazon DynamoDB with AWS PrivateLink | Amazon Web Services
19 March 2024, AWS Blog

Introducing configurable maximum throughput for Amazon DynamoDB on-demand | Amazon Web Services
3 May 2024, AWS Blog

A new and improved AWS CDK construct for Amazon DynamoDB tables | Amazon Web Services
31 January 2024, AWS Blog

provided by Google News

Exploring new features of Apache TinkerPop 3.7.x in Amazon Neptune | Amazon Web Services
7 June 2024, AWS Blog

Building NHM London's Planetary Knowledge Base with Amazon Neptune and the Registry of Open Data on AWS ...
5 June 2024, AWS Blog

Unit testing Apache TinkerPop transactions: From TinkerGraph to Amazon Neptune | Amazon Web Services
3 June 2024, AWS Blog

AWS announces Amazon Neptune I/O-Optimized
22 February 2024, AWS Blog

AWS Weekly Roundup: LlamaIndex support for Amazon Neptune, force AWS CloudFormation stack deletion, and more ...
27 May 2024, AWS Blog

provided by Google News

Big Data Analytics: A Game Changer for Infrastructure
13 July 2023, Spiceworks News and Insights

HEAVY.AI Launches HEAVY 7.0, Introducing Real-Time Machine Learning Capabilities
19 April 2023, businesswire.com

HEAVY.AI Partners with Bain, Maxar, and Nvidia to Provide Digital Twins for Telecom Networks
16 February 2023, Datanami

Making the most of geospatial intelligence
14 April 2023, InfoWorld

The insideBIGDATA IMPACT 50 List for Q4 2023
11 October 2023, insideBIGDATA

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

Neo4j logo

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

Milvus logo

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

Present your product here