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DBMS > Amazon DynamoDB vs. Microsoft Access vs. Sphinx vs. Splice Machine

System Properties Comparison Amazon DynamoDB vs. Microsoft Access vs. Sphinx vs. Splice Machine

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Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonMicrosoft Access  Xexclude from comparisonSphinx  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudMicrosoft Access combines a backend RDBMS (JET / ACE Engine) with a GUI frontend for data manipulation and queries. infoThe Access frontend is often used for accessing other datasources (DBMS, Excel, etc.)Open source search engine for searching in data from different sources, e.g. relational databasesOpen-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
Relational DBMSSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score77.57
Rank#16  Overall
#2  Document stores
#2  Key-value stores
Score105.40
Rank#11  Overall
#8  Relational DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Score0.54
Rank#255  Overall
#116  Relational DBMS
Websiteaws.amazon.com/­dynamodbwww.microsoft.com/­en-us/­microsoft-365/­accesssphinxsearch.comsplicemachine.com
Technical documentationdocs.aws.amazon.com/­dynamodbdeveloper.microsoft.com/­en-us/­accesssphinxsearch.com/­docssplicemachine.com/­how-it-works
DeveloperAmazonMicrosoftSphinx Technologies Inc.Splice Machine
Initial release2012199220012014
Current release1902 (16.0.11328.20222), March 20193.5.1, February 20233.1, March 2021
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationscommercial infoBundled with Microsoft OfficeOpen Source infoGPL version 2, commercial licence availableOpen Source infoAGPL 3.0, commercial license available
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C++Java
Server operating systemshostedWindows infoNot a real database server, but making use of DLLsFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesnoyes
Secondary indexesyesyesyes infofull-text index on all search fieldsyes
SQL infoSupport of SQLnoyes infobut not compliant to any SQL standardSQL-like query language (SphinxQL)yes
APIs and other access methodsRESTful HTTP APIADO.NET
DAO
ODBC
OLE DB
Proprietary protocolJDBC
Native Spark Datasource
ODBC
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
C
C#
C++
Delphi
Java (JDBC-ODBC)
VBA
Visual Basic.NET
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
Server-side scripts infoStored proceduresnoyes infosince Access 2010 using the ACE-enginenoyes infoJava
Triggersyes infoby integration with AWS Lambdayes infosince Access 2010 using the ACE-enginenoyes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infoPartitioning is done manually, search queries against distributed index is supportedShared Nothhing Auto-Sharding, Columnar Partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesnonenoneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonoYes, via Full Spark Integration
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate Consistency
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 regionACID infobut no files for transaction loggingnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyes infobut no files for transaction loggingyes infoThe original contents of fields are not stored in the Sphinx index.yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)no infoa simple user-level security was built in till version Access 2003noAccess rights for users, groups and roles according to SQL-standard

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More resources
Amazon DynamoDBMicrosoft AccessSphinxSplice Machine
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