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DBMS > Amazon SimpleDB vs. Dragonfly vs. Google Cloud Bigtable vs. H2

System Properties Comparison Amazon SimpleDB vs. Dragonfly vs. Google Cloud Bigtable vs. H2

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Editorial information provided by DB-Engines
NameAmazon SimpleDB  Xexclude from comparisonDragonfly  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonH2  Xexclude from comparison
DescriptionHosted simple database service by Amazon, with the data stored in the Amazon Cloud. infoThere is an unrelated product called SimpleDB developed by Edward ScioreA drop-in Redis replacement that scales vertically to support millions of operations per second and terabyte sized workloads, all on a single instanceGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.
Primary database modelKey-value storeKey-value storeKey-value store
Wide column store
Relational DBMS
Secondary database modelsSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.89
Rank#128  Overall
#22  Key-value stores
Score0.44
Rank#255  Overall
#38  Key-value stores
Score2.97
Rank#92  Overall
#15  Key-value stores
#8  Wide column stores
Score7.57
Rank#47  Overall
#30  Relational DBMS
Websiteaws.amazon.com/­simpledbgithub.com/­dragonflydb/­dragonfly
www.dragonflydb.io
cloud.google.com/­bigtablewww.h2database.com
Technical documentationdocs.aws.amazon.com/­simpledbwww.dragonflydb.io/­docscloud.google.com/­bigtable/­docswww.h2database.com/­html/­main.html
DeveloperAmazonDragonflyDB team and community contributorsGoogleThomas Mueller
Initial release2007202320152005
Current release1.0, March 20232.2.220, July 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSL 1.1commercialOpen Source infodual-licence (Mozilla public license, Eclipse public license)
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java
Server operating systemshostedLinuxhostedAll OS with a Java VM
Data schemeschema-freescheme-freeschema-freeyes
Typing infopredefined data types such as float or datenostrings, hashes, lists, sets, sorted sets, bit arraysnoyes
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.nonono
Secondary indexesyes infoAll columns are indexed automaticallynonoyes
SQL infoSupport of SQLnononoyes
APIs and other access methodsRESTful HTTP APIProprietary protocol infoRESP - REdis Serialization ProtocolgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
JDBC
ODBC
Supported programming languages.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala
C
C#
C++
Clojure
D
Dart
Elixir
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
Objective-C
Perl
PHP
Python
R
Ruby
Rust
Scala
Swift
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
Java
Server-side scripts infoStored proceduresnoLuanoJava Stored Procedures and User-Defined Functions
Triggersnopublish/subscribe channels provide some trigger functionalitynoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoSharding must be implemented in the applicationShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationInternal replication in Colossus, and regional replication between two clusters in different zonesWith clustering: 2 database servers on different computers operate on identical copies of a database
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be specified for read operations
Eventual ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Immediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoConcurrent data updates can be detected by the applicationAtomic execution of command blocks and scriptsAtomic single-row operationsACID
Concurrency infoSupport for concurrent manipulation of datayesyes, strict serializability by the serveryesyes, multi-version concurrency control (MVCC)
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes
User concepts infoAccess controlAccess rights for users and roles can be defined via the AWS Identity and Access Management (IAM)Password-based authenticationAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)fine grained access rights according to SQL-standard

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