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DBMS > Amazon DynamoDB vs. Blazegraph vs. GeoSpock vs. Microsoft Azure Data Explorer vs. Spark SQL

System Properties Comparison Amazon DynamoDB vs. Blazegraph vs. GeoSpock vs. Microsoft Azure Data Explorer vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonBlazegraph  Xexclude from comparisonGeoSpock  Xexclude from comparisonMicrosoft Azure Data Explorer  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.GeoSpock seems to be discontinued. Therefore it will be excluded from the DB-Engines ranking.
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.Spatial and temporal data processing engine for extreme data scaleFully managed big data interactive analytics platformSpark 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 DBMSRelational DBMS infocolumn orientedRelational DBMS
Secondary database modelsTime Series 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
Score0.81
Rank#213  Overall
#19  Graph DBMS
#8  RDF stores
Score3.80
Rank#81  Overall
#43  Relational DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­dynamodbblazegraph.comgeospock.comazure.microsoft.com/­services/­data-explorerspark.apache.org/­sql
Technical documentationdocs.aws.amazon.com/­dynamodbwiki.blazegraph.comdocs.microsoft.com/­en-us/­azure/­data-explorerspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAmazonBlazegraphGeoSpockMicrosoftApache Software Foundation
Initial release2012200620192014
Current release2.1.5, March 20192.0, September 2019cloud service with continuous releases3.5.0 ( 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 serviceyesnoyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, JavascriptScala
Server operating systemshostedLinux
OS X
Windows
hostedhostedLinux
OS X
Windows
Data schemeschema-freeschema-freeyesFixed schema with schema-less datatypes (dynamic)yes
Typing infopredefined data types such as float or dateyesyes infoRDF literal typesyesyes 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.noyesno
Secondary indexesyesyestemporal, categoricalall fields are automatically indexedno
SQL infoSupport of SQLnoSPARQL is used as query languageANSI SQL for query only (using Presto)Kusto Query Language (KQL), SQL subsetSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
JDBCMicrosoft SQL Server communication protocol (MS-TDS)
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
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesnoYes, 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 nodesShardingShardingAutomatic shardingSharding infoImplicit feature of the cloud serviceyes, 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.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-spark
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 configurationImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynoyes infoRelationships in Graphsnonono
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 regionACIDnonono
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.nonono
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)Access rights for users can be defined per tableAzure Active Directory Authenticationno

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Amazon DynamoDBBlazegraphGeoSpockMicrosoft Azure Data ExplorerSpark SQL
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