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DBMS > Amazon DynamoDB vs. Google Cloud Datastore vs. QuestDB vs. Sphinx

System Properties Comparison Amazon DynamoDB vs. Google Cloud Datastore vs. QuestDB vs. Sphinx

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Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonQuestDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudAutomatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA high performance, low latency Time Series DBMSOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument store
Key-value store
Document storeTime Series DBMSSearch engine
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score68.89
Rank#16  Overall
#2  Document stores
#2  Key-value stores
Score5.51
Rank#67  Overall
#10  Document stores
Score0.31
Rank#260  Overall
#20  Time Series DBMS
Score6.35
Rank#59  Overall
#7  Search engines
Websiteaws.amazon.com/­dynamodbcloud.google.com/­datastorequestdb.iosphinxsearch.com
Technical documentationdocs.aws.amazon.com/­dynamodbcloud.google.com/­datastore/­docsquestdb.io/­docs/­introductionsphinxsearch.com/­docs
DeveloperAmazonGoogleQuestDB LimitedSphinx Technologies Inc.
Initial release2012200820142001
Current release3.2.1, January 2020
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationscommercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemshostedhostedLinux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyes, details hereyesno
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 indexesyesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like query language (GQL)SQL-like query languageSQL-like query language (SphinxQL)
APIs and other access methodsRESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP RESTProprietary protocol
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
JavaC++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnousing Google App Enginenono
Triggersyes infoby integration with AWS LambdaCallbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning (by timestamps)Sharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyesMulti-source replication using Paxosnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Immediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate Consistency
Foreign keys infoReferential integritynoyes infovia ReferenceProperties or Ancestor pathsnono
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 infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID for single-table writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes 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.nono
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 based on Google Cloud Identity and Access Management (IAM)no
More information provided by the system vendor
Amazon DynamoDBGoogle Cloud DatastoreQuestDBSphinx
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 DynamoDBGoogle Cloud DatastoreQuestDBSphinx
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