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DBMS > Amazon DynamoDB vs. Blazegraph vs. GridGain

System Properties Comparison Amazon DynamoDB vs. Blazegraph vs. GridGain

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Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonBlazegraph  Xexclude from comparisonGridGain  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.GridGain is an in-memory computing platform, built on Apache Ignite
Primary database modelDocument store
Key-value store
Graph DBMS
RDF store
Key-value store
Relational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score77.57
Rank#16  Overall
#2  Document stores
#2  Key-value stores
Score0.77
Rank#222  Overall
#20  Graph DBMS
#8  RDF stores
Score1.53
Rank#155  Overall
#26  Key-value stores
#73  Relational DBMS
Websiteaws.amazon.com/­dynamodbblazegraph.comwww.gridgain.com
Technical documentationdocs.aws.amazon.com/­dynamodbwiki.blazegraph.comwww.gridgain.com/­docs/­index.html
DeveloperAmazonBlazegraphGridGain Systems, Inc.
Initial release201220062007
Current release2.1.5, March 2019GridGain 8.5.1
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationsOpen Source infoextended commercial license availablecommercial
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaJava, C++, .Net
Server operating systemshostedLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes infoRDF literal 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.yes
Secondary indexesyesyesyes
SQL infoSupport of SQLnoSPARQL is used as query languageANSI-99 for query and DML statements, subset of DDL
APIs and other access methodsRESTful HTTP APIJava API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3
HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
C
C++
Java
JavaScript
PHP
Python
Ruby
C#
C++
Java
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoyesyes (compute grid and cache interceptors can be used instead)
Triggersyes infoby integration with AWS Lambdanoyes (cache interceptors and events)
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesyes (replicated cache)
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyes (compute grid and hadoop accelerator)
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 Consistency
Foreign keys infoReferential integritynoyes infoRelationships in Graphsno
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 regionACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
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)Security Hooks for custom implementations

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More resources
Amazon DynamoDBBlazegraphGridGain
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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

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

Bulk update Amazon DynamoDB tables with AWS Step Functions | 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

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This AI Paper Introduces A Comprehensive RDF Dataset With Over 26 Billion Triples Covering Scholarly Data Across All Scientific Disciplines
19 August 2023, MarkTechPost

Back to the future: Does graph database success hang on query language?
5 March 2018, ZDNet

Harnessing GPUs Delivers a Big Speedup for Graph Analytics
15 December 2015, Datanami

Representation Learning on RDF* and LPG Knowledge Graphs
24 September 2020, Towards Data Science

Faster with GPUs: 5 turbocharged databases
26 September 2016, InfoWorld

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GridGain Announces Call for Speakers for Virtual Apache Ignite Summit 2024
8 February 2024, PR Newswire

GridGain's 2023 Growth Positions Company for Strong 2024
25 January 2024, Datanami

GridGain Named in the 2023 GartnerĀ® Market Guide for Event Stream Processing
22 August 2023, GlobeNewswire

GridGain to Sponsor, Exhibit at Kafka Summit 2024 in London
12 March 2024, PR Newswire

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