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DBMS > Amazon DynamoDB vs. Drizzle vs. Hawkular Metrics vs. Kinetica

System Properties Comparison Amazon DynamoDB vs. Drizzle vs. Hawkular Metrics vs. Kinetica

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Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonDrizzle  Xexclude from comparisonHawkular Metrics  Xexclude from comparisonKinetica  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.Fully vectorized database across both GPUs and CPUs
Primary database modelDocument store
Key-value store
Relational DBMSTime Series DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score74.07
Rank#17  Overall
#3  Document stores
#2  Key-value stores
Score0.00
Rank#379  Overall
#40  Time Series DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websiteaws.amazon.com/­dynamodbwww.hawkular.orgwww.kinetica.com
Technical documentationdocs.aws.amazon.com/­dynamodbwww.hawkular.org/­hawkular-metrics/­docs/­user-guidedocs.kinetica.com
DeveloperAmazonDrizzle project, originally started by Brian AkerCommunity supported by Red HatKinetica
Initial release2012200820142012
Current release7.2.4, September 20127.1, August 2021
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationsOpen Source infoGNU GPLOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++JavaC, C++
Server operating systemshostedFreeBSD
Linux
OS X
Linux
OS X
Windows
Linux
Data schemeschema-freeyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.nono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLnoyes infowith proprietary extensionsnoSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIJDBCHTTP RESTJDBC
ODBC
RESTful HTTP API
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
C
C++
Java
PHP
Go
Java
Python
Ruby
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnononouser defined functions
Triggersyes infoby integration with AWS Lambdano infohooks for callbacks inside the server can be used.yes infovia Hawkular Alertingyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infobased on CassandraSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication
Source-replica replication
selectable replication factor infobased on CassandraSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesnoyes
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 datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Pluggable authentication mechanisms infoe.g. LDAP, HTTPnoAccess rights for users and roles on table level

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More resources
Amazon DynamoDBDrizzleHawkular MetricsKinetica
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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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Waiting for Red Hat OpenShift 4.0? Too late, 4.1 has already arrived… • DEVCLASS
5 June 2019, DevClass

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Kinetica Elevates RAG with Fast Access to Real-Time Data
26 March 2024, Datanami

Kinetica Delivers Real-Time Vector Similarity Search
21 March 2024, insideBIGDATA

Kinetica ramps up RAG for generative AI, empowering enterprises with real-time operational data
18 March 2024, SiliconANGLE News

Kinetica Launches Generative AI Solution for Real-Time Inferencing Powered by NVIDIA AI Enterprise
18 March 2024, GlobeNewswire

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30 October 2023, InfoWorld

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