DB-EnginesInfluxDB: Focus on building software with an easy-to-use serverless, scalable time series platformEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Amazon Aurora vs. EJDB vs. Google Cloud Bigtable vs. Machbase Neo

System Properties Comparison Amazon Aurora vs. EJDB vs. Google Cloud Bigtable vs. Machbase Neo

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonEJDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonMachbase Neo infoFormer name was Infiniflux  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonEmbeddable document-store database library with JSON representation of queries (in MongoDB style)Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.TimeSeries DBMS for AIoT and BigData
Primary database modelRelational DBMSDocument storeKey-value store
Wide column store
Time Series DBMS
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score0.27
Rank#297  Overall
#44  Document stores
Score3.26
Rank#92  Overall
#13  Key-value stores
#8  Wide column stores
Score0.12
Rank#339  Overall
#30  Time Series DBMS
Websiteaws.amazon.com/­rds/­auroragithub.com/­Softmotions/­ejdbcloud.google.com/­bigtablemachbase.com
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlgithub.com/­Softmotions/­ejdb/­blob/­master/­README.mdcloud.google.com/­bigtable/­docsmachbase.com/­dbms
DeveloperAmazonSoftmotionsGoogleMachbase
Initial release2015201220152013
Current releaseV8.0, August 2023
License infoCommercial or Open SourcecommercialOpen Source infoGPLv2commercialcommercial infofree test version available
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 languageCC
Server operating systemshostedserver-lesshostedLinux
macOS
Windows
Data schemeyesschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, bool, date, object_idnoyes
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.yesnono
Secondary indexesyesnonoyes
SQL infoSupport of SQLyesnonoSQL-like query language
APIs and other access methodsADO.NET
JDBC
ODBC
in-process shared librarygRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby
C#
C++
Go
Java
JavaScript (Node.js)
Python
C
C#
C++
Go
Java
JavaScript
PHP infovia ODBC
Python
R infovia ODBC
Scala
Server-side scripts infoStored proceduresyesnonono
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnoneShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneInternal replication in Colossus, and regional replication between two clusters in different zonesselectable replication factor
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)
Foreign keys infoReferential integrityyesno infotypically not needed, however similar functionality with collection joins possiblenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoAtomic single-row operationsno
Concurrency infoSupport for concurrent manipulation of datayesyes infoRead/Write Lockingyesyes
Durability infoSupport for making data persistentyesyesyesno
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infovolatile and lookup table
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

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Amazon AuroraEJDBGoogle Cloud BigtableMachbase Neo infoFormer name was Infiniflux
DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

Amazon - the rising star in the DBMS market
3 August 2015, Matthias Gelbmann

show all

Recent citations in the news

How LeadSquared accelerated chatbot deployments with generative AI using Amazon Bedrock and Amazon Aurora ...
24 May 2024, AWS Blog

Continuously replicate Amazon DynamoDB changes to Amazon Aurora PostgreSQL using AWS Lambda | Amazon ...
14 May 2024, AWS Blog

Join the preview of Amazon Aurora Limitless Database | Amazon Web Services
27 November 2023, AWS Blog

Amazon Aurora MySQL version 2 (with MySQL 5.7 compatibility) to version 3 (with MySQL 8.0 compatibility) upgrade ...
18 March 2024, AWS Blog

Build generative AI applications with Amazon Aurora and Knowledge Bases for Amazon Bedrock | Amazon Web Services
2 February 2024, AWS Blog

provided by Google News

Google's AI-First Strategy Brings Vector Support To Cloud Databases
1 March 2024, Forbes

Google Introduces Autoscaling for Cloud Bigtable for Optimizing Costs
31 January 2022, InfoQ.com

Review: Google Bigtable scales with ease
7 September 2016, InfoWorld

Google scales up Cloud Bigtable NoSQL database
27 January 2022, TechTarget

Google introduces Cloud Bigtable managed NoSQL database to process data at scale
6 May 2015, VentureBeat

provided by Google News



Share this page

Featured Products

AllegroGraph logo

Graph Database Leader for AI Knowledge Graph Applications - The Most Secure Graph Database Available.
Free Download

Neo4j logo

See for yourself how a graph database can make your life easier.
Use Neo4j online for free.

Milvus logo

Vector database designed for GenAI, fully equipped for enterprise implementation.
Try Managed Milvus for Free

RaimaDB logo

RaimaDB, embedded database for mission-critical applications. When performance, footprint and reliability matters.
Try RaimaDB for free.

Datastax Astra logo

Bring all your data to Generative AI applications with vector search enabled by the most scalable
vector database available.
Try for Free

Present your product here