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DBMS > Amazon Aurora vs. Blueflood vs. Google Cloud Bigtable vs. KeyDB

System Properties Comparison Amazon Aurora vs. Blueflood vs. Google Cloud Bigtable vs. KeyDB

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonBlueflood  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonKeyDB  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonScalable TimeSeries DBMS based on CassandraGoogle's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols
Primary database modelRelational DBMSTime Series DBMSKey-value store
Wide column store
Key-value store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.57
Rank#51  Overall
#32  Relational DBMS
Score0.13
Rank#346  Overall
#33  Time Series DBMS
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.70
Rank#229  Overall
#32  Key-value stores
Websiteaws.amazon.com/­rds/­aurorablueflood.iocloud.google.com/­bigtablegithub.com/­Snapchat/­KeyDB
keydb.dev
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlgithub.com/­rax-maas/­blueflood/­wikicloud.google.com/­bigtable/­docsdocs.keydb.dev
DeveloperAmazonRackspaceGoogleEQ Alpha Technology Ltd.
Initial release2015201320152019
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoBSD-3
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC++
Server operating systemshostedLinux
OS X
hostedLinux
Data schemeyespredefined schemeschema-freeschema-free
Typing infopredefined data types such as float or dateyesyesnopartial infoSupported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes
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.yesnonono
Secondary indexesyesnonoyes infoby using the Redis Search module
SQL infoSupport of SQLyesnonono
APIs and other access methodsADO.NET
JDBC
ODBC
HTTP RESTgRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
Proprietary protocol infoRESP - REdis Serialization Protoco
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic
Server-side scripts infoStored proceduresyesnonoLua
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningSharding infobased on CassandraShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationselectable replication factor infobased on CassandraInternal replication in Colossus, and regional replication between two clusters in different zonesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infobased on Cassandra
Immediate Consistency infobased on Cassandra
Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Strong eventual consistency with CRDTs
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoAtomic single-row operationsOptimistic locking, atomic execution of commands blocks and scripts
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoConfigurable mechanisms for persistency via snapshots and/or operations logs
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)simple password-based access control and ACL

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More resources
Amazon AuroraBluefloodGoogle Cloud BigtableKeyDB
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