DBMS > AgensGraph vs. Amazon DynamoDB vs. Google Cloud Bigtable vs. InfluxDB

System Properties Comparison AgensGraph vs. Amazon DynamoDB vs. Google Cloud Bigtable vs. InfluxDB

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

Hosted, scalable database service by Amazon with the data stored in Amazons cloud

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

DBMS for storing time series, events and metrics

Primary database model

Graph DBMS
Relational DBMS

Document store
Key-value store

Key-value store
Wide column store

Time Series DBMS

Secondary database models

Spatial DBMS

with GEO package

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.16
Rank	#333	Overall
	#30	Graph DBMS
	#146	Relational DBMS

Score	77.57
Rank	#16	Overall
	#2	Document stores
	#2	Key-value stores

Score	3.58
Rank	#92	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	26.56
Rank	#28	Overall
	#1	Time Series DBMS

Website

bitnine.net/agensgraph

aws.amazon.com/dynamodb

cloud.google.com/bigtable

www.influxdata.com/products/influxdb-overview

Technical documentation

bitnine.net/documentation

docs.aws.amazon.com/dynamodb

cloud.google.com/bigtable/docs

docs.influxdata.com/influxdb

Developer

Bitnine Global Inc.

Amazon

Google

Initial release

2016

2012

2015

2013

Current release

2.1, December 2018

2.7.5, January 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

free tier for a limited amount of database operations

commercial

Open Source

MIT-License; commercial enterprise version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Server operating systems

Linux
OS X
Windows

hosted

Linux
OS X

through Homebrew

Data scheme

depending on used data model

schema-free

Typing

predefined data types such as float or date

yes

Numeric data and Strings

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

Cypher Query Language
JDBC

RESTful HTTP API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

HTTP API
JSON over UDP

Supported programming languages

C
Java
JavaScript
Python

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C#
C++
Go
Java
JavaScript (Node.js)
Python

.Net
Clojure
Erlang
Go
Haskell
Java
JavaScript
JavaScript (Node.js)
Lisp
Perl
PHP
Python
R
Ruby
Rust
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes

by integration with AWS Lambda

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

in enterprise version only

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Internal replication in Colossus, and regional replication between two clusters in different zones

selectable replication factor

in enterprise version only

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

ACID across one or more tables within a single AWS account and region

Atomic single-row operations

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

Depending on used storage engine

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

simple rights management via user accounts

More information provided by the system vendor

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