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DBMS > Amazon DynamoDB vs. Faircom DB vs. Postgres-XL vs. Quasardb vs. Splice Machine

System Properties Comparison Amazon DynamoDB vs. Faircom DB vs. Postgres-XL vs. Quasardb vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonPostgres-XL  Xexclude from comparisonQuasardb  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Based on PostgreSQL enhanced with MPP and write-scale-out cluster featuresDistributed, high-performance timeseries databaseOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark
Primary database modelDocument store
Key-value store
Key-value store
Relational DBMS
Relational DBMSTime Series DBMSRelational DBMS
Secondary database modelsDocument 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
Score0.20
Rank#318  Overall
#48  Key-value stores
#141  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score0.14
Rank#332  Overall
#29  Time Series DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Websiteaws.amazon.com/­dynamodbwww.faircom.com/­products/­faircom-dbwww.postgres-xl.orgquasar.aisplicemachine.com
Technical documentationdocs.aws.amazon.com/­dynamodbdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmlwww.postgres-xl.org/­documentationdoc.quasar.ai/­mastersplicemachine.com/­how-it-works
DeveloperAmazonFairCom CorporationquasardbSplice Machine
Initial release201219792014 infosince 2012, originally named StormDB20092014
Current releaseV12, November 202010 R1, October 20183.14.1, January 20243.1, March 2021
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationscommercial infoRestricted, free version availableOpen Source infoMozilla public licensecommercial infoFree community edition, Non-profit organizations and non-commercial usage are eligible for free licensesOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++CC++Java
Server operating systemshostedAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
Linux
macOS
BSD
Linux
OS X
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeschema free, schema optional, schema required, partial schema,yesschema-freeyes
Typing infopredefined data types such as float or dateyesyes, ANSI SQL Types, JSON, typed binary structuresyesyes infointeger and binaryyes
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 infoXML type, but no XML query functionalityno
Secondary indexesyesyesyesyes infowith tagsyes
SQL infoSupport of SQLnoyes, ANSI SQL with proprietary extensionsyes infodistributed, parallel query executionSQL-like query languageyes
APIs and other access methodsRESTful HTTP APIADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP APIJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes info.Net, JavaScript, C/C++user defined functionsnoyes infoJava
Triggersyes infoby integration with AWS Lambdayesyesnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioninghorizontal partitioningSharding infoconsistent hashingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes, configurable to be parallel or serial, synchronous or asynchronous, uni-directional or bi-directional, ACID-consistent or eventually consistent (with custom conflict resolution).Source-replica replication with selectable replication factorMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonowith Hadoop integrationYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesnoyes
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 regiontunable from ACID to Eventually ConsistentACID infoMVCCACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesYes, tunable from durable to delayed durability to in-memoryyesyes infoby using LevelDByes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoTransient modeyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Fine grained access rights according to SQL-standard with additional protections for filesfine grained access rights according to SQL-standardCryptographically strong user authentication and audit trailAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon DynamoDBFaircom DB infoformerly c-treeACEPostgres-XLQuasardbSplice Machine
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