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DBMS > Amazon DynamoDB vs. Amazon SimpleDB vs. Faircom DB vs. Kinetica vs. Splice Machine

System Properties Comparison Amazon DynamoDB vs. Amazon SimpleDB vs. Faircom DB vs. Kinetica vs. Splice Machine

Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonAmazon SimpleDB  Xexclude from comparisonFaircom DB infoformerly c-treeACE  Xexclude from comparisonKinetica  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudHosted simple database service by Amazon, with the data stored in the Amazon Cloud. infoThere is an unrelated product called SimpleDB developed by Edward ScioreNative high-speed multi-model DBMS for relational and key-value store data simultaneously accessible through SQL and NoSQL APIs.Fully vectorized database across both GPUs and CPUsOpen-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 storeKey-value store
Relational DBMS
Relational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score74.45
Rank#17  Overall
#3  Document stores
#2  Key-value stores
Score1.88
Rank#133  Overall
#23  Key-value stores
Score0.29
Rank#304  Overall
#43  Key-value stores
#136  Relational DBMS
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.54
Rank#252  Overall
#115  Relational DBMS
Websiteaws.amazon.com/­dynamodbaws.amazon.com/­simpledbwww.faircom.com/­products/­faircom-dbwww.kinetica.comsplicemachine.com
Technical documentationdocs.aws.amazon.com/­dynamodbdocs.aws.amazon.com/­simpledbdocs.faircom.com/­docs/­en/­UUID-7446ae34-a1a7-c843-c894-d5322e395184.htmldocs.kinetica.comsplicemachine.com/­how-it-works
DeveloperAmazonAmazonFairCom CorporationKineticaSplice Machine
Initial release20122007197920122014
Current releaseV12, November 20207.1, August 20213.1, March 2021
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationscommercialcommercial infoRestricted, free version availablecommercialOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageANSI C, C++C, C++Java
Server operating systemshostedhostedAIX
FreeBSD
HP-UX
Linux
NetBSD
OS X
QNX
SCO
Solaris
VxWorks
Windows infoeasily portable to other OSs
LinuxLinux
OS X
Solaris
Windows
Data schemeschema-freeschema-freeschema free, schema optional, schema required, partial schema,yesyes
Typing infopredefined data types such as float or dateyesnoyes, ANSI SQL Types, JSON, typed binary structuresyesyes
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 indexesyesyes infoAll columns are indexed automaticallyyesyesyes
SQL infoSupport of SQLnonoyes, ANSI SQL with proprietary extensionsSQL-like DML and DDL statementsyes
APIs and other access methodsRESTful HTTP APIRESTful HTTP APIADO.NET
Direct SQL
JDBC
JPA
ODBC
RESTful HTTP/JSON API
RESTful MQTT/JSON API
RPC
JDBC
ODBC
RESTful HTTP API
JDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
.Net
C
C#
C++
Java
JavaScript (Node.js and browser)
PHP
Python
Visual Basic
C++
Java
JavaScript (Node.js)
Python
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnonoyes info.Net, JavaScript, C/C++user defined functionsyes infoJava
Triggersyes infoby integration with AWS Lambdanoyesyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoSharding must be implemented in the applicationFile partitioning, horizontal partitioning, sharding infoCustomizable business rules for table partitioningShardingShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesyes, 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 replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nononoYes, 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 infocan be specified for read operations
Eventual Consistency
Immediate Consistency
Tunable consistency per server, database, table, and transaction
Immediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonoyesyesyes
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 infoConcurrent data updates can be detected by the applicationtunable from ACID to Eventually ConsistentnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesYes, tunable from durable to delayed durability to in-memoryyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Access 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 filesAccess rights for users and roles on table levelAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon DynamoDBAmazon SimpleDBFaircom DB infoformerly c-treeACEKineticaSplice Machine
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