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DBMS > Amazon DynamoDB vs. QuestDB vs. Sphinx

System Properties Comparison Amazon DynamoDB vs. QuestDB vs. Sphinx

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Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonQuestDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudA high performance open source SQL database for time series dataOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Key-value store
Time Series DBMSSearch engine
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score69.14
Rank#17  Overall
#2  Document stores
#2  Key-value stores
Score0.37
Rank#247  Overall
#19  Time Series DBMS
Score6.43
Rank#60  Overall
#7  Search engines
Websiteaws.amazon.com/­dynamodbquestdb.iosphinxsearch.com
Technical documentationdocs.aws.amazon.com/­dynamodbquestdb.io/­docs/­introductionsphinxsearch.com/­docs
DeveloperAmazonQuestDB LimitedSphinx Technologies Inc.
Initial release201220142001
Current release3.3.1, July 2020
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationsOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++
Server operating systemshostedLinux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyes infoschema-free via InfluxDB Line Protocolyes
Typing infopredefined data types such as float or dateyesyesno
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.no
Secondary indexesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like query languageSQL-like query language (SphinxQL)
APIs and other access methodsRESTful HTTP APIHTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
Proprietary protocol
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
C infoPostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust infoover HTTP
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnonono
Triggersyes infoby integration with AWS Lambdanono
Partitioning methods infoMethods for storing different data on different nodesShardinghorizontal partitioning (by timestamps)Sharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesConfigurable consistency for N replicasnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate Consistency
Foreign keys infoReferential integritynonono
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 for single-table writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infothrough memory mapped files
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)no
More information provided by the system vendor
Amazon DynamoDBQuestDBSphinx
Specific characteristicsRelational model with native time series support Column based storage and time partitioned...
» more
Competitive advantagesReal-time data ingestion and istant SQL queries for time series High performance...
» more
Typical application scenariosApplication metrics Financial market data and algo trading DevOps monitoring Real-time...
» more
Licensing and pricing modelsApache 2.0.
» more

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More resources
Amazon DynamoDBQuestDBSphinx
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