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DBMS > Amazon DynamoDB vs. Apache Cassandra vs. Databricks

System Properties Comparison Amazon DynamoDB vs. Apache Cassandra vs. Databricks

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Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonApache Cassandra  Xexclude from comparisonDatabricks  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudWide-column store based on ideas of BigTable and DynamoDB infoOptimized for write accessThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.
Primary database modelDocument store
Key-value store
Wide column storeDocument store
Relational DBMS
Secondary database modelsVector DBMS infostarting with release V5
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score76.49
Rank#15  Overall
#3  Document stores
#2  Key-value stores
Score108.21
Rank#11  Overall
#1  Wide column stores
Score99.29
Rank#12  Overall
#2  Document stores
#8  Relational DBMS
Websiteaws.amazon.com/­dynamodbcassandra.apache.orgwww.databricks.com
Technical documentationdocs.aws.amazon.com/­dynamodbcassandra.apache.org/­doc/­latestdocs.databricks.com
DeveloperAmazonApache Software Foundation infoApache top level project, originally developped by FacebookDatabricks
Initial release201220082013
Current release5.0-rc1, July 2024
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationsOpen Source infoApache version 2commercial
Cloud-based only infoOnly available as a cloud serviceyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava
Server operating systemshostedBSD
Linux
OS X
Windows
hosted
Data schemeschema-freeschema-freeFlexible Schema (defined schema, partial schema, schema free)
Typing infopredefined data types such as float or dateyesyes
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.noyes
Secondary indexesyesrestricted infoonly equality queries, not always the best performing solutionyes
SQL infoSupport of SQLnoSQL-like SELECT, DML and DDL statements (CQL)with Databricks SQL
APIs and other access methodsRESTful HTTP APIProprietary protocol infoCQL (Cassandra Query Language, an SQL-like language)
Thrift
JDBC
ODBC
RESTful HTTP API
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript infoNode.js
Perl
PHP
Python
Ruby
Scala
Python
R
Scala
Server-side scripts infoStored proceduresnonouser defined functions and aggregates
Triggersyes infoby integration with AWS Lambdayes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infono "single point of failure"
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factor infoRepresentation of geographical distribution of servers is possibleyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual Consistency
Immediate Consistency infocan be individually decided for each write operation
Immediate Consistency
Foreign keys infoReferential integritynono
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 regionno infoAtomicity and isolation are supported for single operationsACID
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.nono
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users can be defined per object
More information provided by the system vendor
Amazon DynamoDBApache CassandraDatabricks
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