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

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

Editorial information provided by DB-Engines
NameAmazon DynamoDB  Xexclude from comparisonDrizzle  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonQuestDB  Xexclude from comparisonSphinx  Xexclude from comparison
Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.
DescriptionHosted, scalable database service by Amazon with the data stored in Amazons cloudMySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA 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
Relational DBMSDocument storeTime Series DBMSSearch engine
Secondary database modelsRelational 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
Score4.49
Rank#79  Overall
#12  Document stores
Score2.48
Rank#115  Overall
#9  Time Series DBMS
Score6.03
Rank#60  Overall
#6  Search engines
Websiteaws.amazon.com/­dynamodbcloud.google.com/­datastorequestdb.iosphinxsearch.com
Technical documentationdocs.aws.amazon.com/­dynamodbcloud.google.com/­datastore/­docsquestdb.io/­docssphinxsearch.com/­docs
DeveloperAmazonDrizzle project, originally started by Brian AkerGoogleQuestDB Technology IncSphinx Technologies Inc.
Initial release20122008200820142001
Current release7.2.4, September 20123.5.1, February 2023
License infoCommercial or Open Sourcecommercial infofree tier for a limited amount of database operationsOpen Source infoGNU GPLcommercialOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++Java (Zero-GC), C++, RustC++
Server operating systemshostedFreeBSD
Linux
OS X
hostedLinux
macOS
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeyesschema-freeyes infoschema-free via InfluxDB Line Protocolyes
Typing infopredefined data types such as float or dateyesyesyes, 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 indexesyesyesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLnoyes infowith proprietary extensionsSQL-like query language (GQL)SQL with time-series extensionsSQL-like query language (SphinxQL)
APIs and other access methodsRESTful HTTP APIJDBCgRPC (using protocol buffers) API
RESTful HTTP/JSON API
HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol
Proprietary protocol
Supported programming languages.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby
C
C++
Java
PHP
.Net
Go
Java
JavaScript (Node.js)
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 proceduresnonousing Google App Enginenono
Triggersyes infoby integration with AWS Lambdano infohooks for callbacks inside the server can be used.Callbacks using the Google Apps Enginenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardinghorizontal 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
Source-replica replication
Multi-source replication using PaxosSource-replica replication with eventual consistencynone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyes 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 integritynoyesyes 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 regionACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID for single-table writesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.noyes infothrough memory mapped files
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Pluggable authentication mechanisms infoe.g. LDAP, HTTPAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)no
More information provided by the system vendor
Amazon DynamoDBDrizzleGoogle Cloud DatastoreQuestDBSphinx
Specific characteristicsRelational model with native time series support Column-based storage and time partitioned...
» more
Competitive advantagesHigh ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more
Typical application scenariosFinancial tick data Industrial IoT Application Metrics Monitoring
» more
Key customersBanks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more
Licensing and pricing modelsOpen source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more
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