DB-EnginesExtremeDB: mitigate connectivity issues in a DBMSEnglish
Deutsch
Knowledge Base of Relational and NoSQL Database Management Systemsprovided by solid IT

DBMS > Amazon Aurora vs. BoltDB vs. Google Cloud Bigtable vs. NSDb

System Properties Comparison Amazon Aurora vs. BoltDB vs. Google Cloud Bigtable vs. NSDb

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonBoltDB  Xexclude from comparisonGoogle Cloud Bigtable  Xexclude from comparisonNSDb  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonAn embedded key-value store for Go.Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes
Primary database modelRelational DBMSKey-value 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
Score7.57
Rank#51  Overall
#32  Relational DBMS
Score0.80
Rank#215  Overall
#31  Key-value stores
Score3.15
Rank#95  Overall
#14  Key-value stores
#8  Wide column stores
Score0.08
Rank#369  Overall
#40  Time Series DBMS
Websiteaws.amazon.com/­rds/­auroragithub.com/­boltdb/­boltcloud.google.com/­bigtablensdb.io
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlcloud.google.com/­bigtable/­docsnsdb.io/­Architecture
DeveloperAmazonGoogle
Initial release2015201320152017
License infoCommercial or Open SourcecommercialOpen Source infoMIT LicensecommercialOpen Source infoApache Version 2.0
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 languageGoJava, Scala
Server operating systemshostedBSD
Linux
OS X
Solaris
Windows
hostedLinux
macOS
Data schemeyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesnonoyes: int, bigint, decimal, string
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 indexesyesnonoall fields are automatically indexed
SQL infoSupport of SQLyesnonoSQL-like query language
APIs and other access methodsADO.NET
JDBC
ODBC
gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)
gRPC
HTTP REST
WebSocket
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
GoC#
C++
Go
Java
JavaScript (Node.js)
Python
Java
Scala
Server-side scripts infoStored proceduresyesnonono
Triggersyesnono
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 zones
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencynoneImmediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)Eventual Consistency
Foreign keys infoReferential integrityyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDyesAtomic single-row operationsno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesUsing Apache Lucene
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnono
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)

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 AuroraBoltDBGoogle Cloud BigtableNSDb
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

Introducing the Advanced Python Wrapper Driver for Amazon Aurora | Amazon Web Services
11 June 2024, AWS Blog

Build a FedRAMP compliant generative AI-powered chatbot using Amazon Aurora Machine Learning and Amazon ...
10 June 2024, AWS Blog

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

Improve the performance of generative AI workloads on Amazon Aurora with Optimized Reads and pgvector | Amazon ...
9 February 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

What I learnt from building 3 high traffic web applications on an embedded key value store.
21 February 2018, hackernoon.com

4 Instructive Postmortems on Data Downtime and Loss
1 March 2024, The Hacker News

Roblox’s cloud-native catastrophe: A post mortem
31 January 2022, InfoWorld

How to Put a GUI on Ansible, Using Semaphore
22 April 2023, The New Stack

Grafana Loki: Architecture Summary and Running in Kubernetes
14 March 2023, hackernoon.com

provided by Google News

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

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

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

Google Cloud makes it cheaper to run smaller workloads on Bigtable
7 April 2020, TechCrunch

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

Neo4j logo

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

Milvus logo

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

Present your product here