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DBMS > Amazon DynamoDB vs. Blazegraph vs. Microsoft Azure Data Explorer vs. Raima Database Manager vs. Spark SQL

System Properties Comparison Amazon DynamoDB vs. Blazegraph vs. Microsoft Azure Data Explorer vs. Raima Database Manager vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonBlazegraph  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonRaima Database Manager infoformerly named db_Vista  Xexclude from comparisonSpark SQL  Xexclude from comparison
Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudHigh-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.Fully managed big data interactive analytics platformRDBMS with a small footprint, either embedded into an application or used as a database serverSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Graph DBMS
RDF store
Relational DBMS infocolumn orientedRelational DBMS
Time Series DBMS
Relational 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
Score74.45
Rank#17  Overall
#3  Document stores
#2  Key-value stores
Score0.81
Rank#213  Overall
#19  Graph DBMS
#8  RDF stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score0.49
Rank#259  Overall
#121  Relational DBMS
#21  Time Series DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­dynamodbblazegraph.comazure.microsoft.com/­services/­data-explorerraima.comspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­dynamodbwiki.blazegraph.comdocs.microsoft.com/­en-us/­azure/­data-explorerdocs.raima.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonBlazegraphMicrosoftRaima Inc.Apache Software Foundation
Initial release20122006201919842014
Current release2.1.5, March 2019cloud service with continuous releases15, June 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationsOpen Source infoextended commercial license availablecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCScala
Server operating systemshostedLinux
OS X
Windows
hostedAndroid
HP-UX
Integrity RTOS
iOS
Linux
OS X
QNX
Solaris
VxWorks
Windows
Linux
OS X
Windows
Data schemeschema-freeschema-freeFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or dateyesyes infoRDF literal typesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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.yesno infoExporting/Importing of XML structures possibleno
Secondary indexesyesyesall fields are automatically indexedyesno
SQL infoSupport of SQLnoSPARQL is used as query languageKusto Query Language (KQL), SQL subsetyesSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Objective-C
PL/SQL
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesYes, possible languages: KQL, Python, Ryes infobased on the ANSI/ISO SQL Persistent Stored Modules (PSM) specificationno
Triggersyes infoby integration with AWS Lambdanoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infoImplicit feature of the cloud servicehorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noSpark 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 Consistency or Eventual Consistency depending on configurationEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyes infoRelationships in Graphsnoyesno
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 regionACIDnoACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
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.noyesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Security and Authentication via Web Application Container (Tomcat, Jetty)Azure Active Directory Authenticationnono
More information provided by the system vendor
Amazon DynamoDBBlazegraphMicrosoft Azure Data ExplorerRaima Database Manager infoformerly named db_VistaSpark SQL
Specific characteristicsRaima Database Manager (RDM) is an embedded time-series database optimized to run...
» more
Competitive advantagesDecreased time-to-market Industry-standard interfaces & tools for making your job...
» more
Typical application scenariosTypical use cases include: Internet of Things (IoT) Embedded In-Memory Database Time-Series...
» more
Key customersInfor, ABB, The Boeing Company, BAE Systems, Dow Jones, Dun & Bradstreet, Fujitsu,...
» more
Market metricsOver 30 000 applications developers worldwide have field-tested RDM products More...
» more
Licensing and pricing modelsJust as the technical aspects of Raima Database Manager are flexible, so are the...
» more
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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.

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More resources
Amazon DynamoDBBlazegraphMicrosoft Azure Data ExplorerRaima Database Manager infoformerly named db_VistaSpark SQL
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