DBMS > Amazon DynamoDB vs. Bangdb vs. Couchbase vs. GraphDB vs. TypeDB

System Properties Comparison Amazon DynamoDB vs. Bangdb vs. Couchbase vs. GraphDB vs. TypeDB

Editorial information provided by DB-Engines

Name

Description

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

Converged and high performance database for device data, events, time series, document and graph

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Document store
Key-value store

Document store
Graph DBMS
Time Series DBMS

Document store

Graph DBMS
RDF store

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Secondary database models

Spatial DBMS

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

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

Score	74.45
Rank	#17	Overall
	#3	Document stores
	#2	Key-value stores

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	16.59
Rank	#36	Overall
	#5	Document stores

Score	3.25
Rank	#91	Overall
	#7	Graph DBMS
	#4	RDF stores

Score	0.70
Rank	#230	Overall
	#20	Graph DBMS
	#106	Relational DBMS

Website

aws.amazon.com/dynamodb

Technical documentation

docs.aws.amazon.com/dynamodb

docs.bangdb.com

docs.couchbase.com

graphdb.ontotext.com/documentation

typedb.com/docs

Social network pages

Developer

Amazon

Sachin Sinha, BangDB

Couchbase, Inc.

Ontotext

Vaticle

Initial release

2012

2011

2000

2016

Current release

BangDB 2.0, October 2021

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

10.4, October 2023

2.26.3, January 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

Open Source

BSD 3

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

commercial

Some plugins of GraphDB Workbench are open sourced

Open Source

GPL Version 3, commercial licenses 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

C, C++

C, C++, Go and Erlang

Java

Server operating systems

hosted

Linux

Linux
OS X
Windows

All OS with a Java VM
Linux
OS X
Windows

Linux
OS X
Windows

Data scheme

schema-free

schema-free and OWL/RDFS-schema support; RDF shapes

yes

Typing

predefined data types such as float or date

yes

yes: string, long, double, int, geospatial, stream, events

yes

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

secondary, composite, nested, reverse, geospatial

yes

yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes

yes

SQL

Support of SQL

SQL like support with command line tool

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

APIs and other access methods

RESTful HTTP API

Proprietary protocol
RESTful HTTP API

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C
C#
C++
Java
Python

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

well-defined plugin interfaces; JavaScript server-side extensibility

Triggers

yes

by integration with AWS Lambda

yes, Notifications (with Streaming only)

yes

via the TAP protocol

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Automatic Sharding

none

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor, Knob for CAP (enterprise version only)

Multi-source replication

including cross data center replication
Source-replica replication

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

yes

by using Apache Kafka and Apache Zookeeper

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Tunable consistency, set CAP knob accordingly

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)

Immediate Consistency

Foreign keys

Referential integrity

yes

Constraint checking

substituted by the relationship feature

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

In-memory capabilities

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

yes, run db with in-memory only mode

yes

Ephemeral buckets

User concepts

Access control

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

yes (enterprise version only)

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.

yes

at REST API level; other APIs in progress

More information provided by the system vendor

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Competitive advantages

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