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DBMS > Amazon DynamoDB vs. Apache Impala vs. Datomic vs. FeatureBase vs. Postgres-XL

System Properties Comparison Amazon DynamoDB vs. Apache Impala vs. Datomic vs. FeatureBase vs. Postgres-XL

Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonApache Impala  Xexclude from comparisonDatomic  Xexclude from comparisonFeatureBase  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudAnalytic DBMS for HadoopDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityReal-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.Based on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelDocument store
Key-value store
Relational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial 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
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score0.22
Rank#309  Overall
#139  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Websiteaws.amazon.com/­dynamodbimpala.apache.orgwww.datomic.comwww.featurebase.comwww.postgres-xl.org
Technical documentationdocs.aws.amazon.com/­dynamodbimpala.apache.org/­impala-docs.htmldocs.datomic.comdocs.featurebase.comwww.postgres-xl.org/­documentation
DeveloperAmazonApache Software Foundation infoApache top-level project, originally developed by ClouderaCognitectMolecula and Pilosa Open Source Contributors
Initial release20122013201220172014 infosince 2012, originally named StormDB
Current release4.1.0, June 20221.0.6735, June 20232022, May 202210 R1, October 2018
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationsOpen Source infoApache Version 2commercial infolimited edition freecommercialOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, ClojureGoC
Server operating systemshostedLinuxAll OS with a Java VMLinux
macOS
Linux
macOS
Data schemeschema-freeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.nononoyes infoXML type, but no XML query functionality
Secondary indexesyesyesyesnoyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnoSQL queriesyes infodistributed, parallel query execution
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
RESTful HTTP APIgRPC
JDBC
Kafka Connector
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
All languages supporting JDBC/ODBCClojure
Java
Java
Python
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceyes infoTransaction Functionsuser defined functions
Triggersyes infoby integration with AWS LambdanoBy using transaction functionsnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingnone infoBut extensive use of caching in the application peersShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factornone infoBut extensive use of caching in the application peersyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
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 regionnoACIDyesACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes, using Linux fsyncyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentyesno
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access rights for users, groups and roles infobased on Apache Sentry and Kerberosnofine grained access rights according to SQL-standard

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More resources
Amazon DynamoDBApache ImpalaDatomicFeatureBasePostgres-XL
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