DBMS > Amazon DocumentDB vs. BigchainDB vs. DolphinDB vs. RocksDB

System Properties Comparison Amazon DocumentDB vs. BigchainDB vs. DolphinDB vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Document store

Time Series DBMS

Key-value store

Secondary database models

Relational DBMS

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

Score	1.91
Rank	#132	Overall
	#24	Document stores

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

aws.amazon.com/documentdb

www.bigchaindb.com

www.dolphindb.com

rocksdb.org

Technical documentation

aws.amazon.com/documentdb/resources

bigchaindb.readthedocs.io/en/latest

docs.dolphindb.cn/en/help200/index.html

github.com/facebook/rocksdb/wiki

Developer

DolphinDB, Inc

Facebook, Inc.

Initial release

2019

2016

2018

2013

Current release

v2.00.4, January 2022

8.11.4, April 2024

License

Commercial or Open Source

commercial

Open Source

AGPL v3

commercial

free community version available

Open Source

BSD

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

Python

C++

Server operating systems

hosted

Linux

Linux
Windows

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

SQL

Support of SQL

SQL-like query language

APIs and other access methods

proprietary protocol using JSON (MongoDB compatible)

CLI Client
RESTful HTTP API

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

C++ API
Java API

Supported programming languages

Go
Java
JavaScript (Node.js)
PHP
Python

Go
Haskell
Java
JavaScript
Python
Ruby

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

selectable replication factor

yes

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

Foreign keys

Referential integrity

typically not used, however similar functionality with DBRef possible

Transaction concepts

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

Atomic single-document operations

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes,with MongoDB ord RethinkDB

yes

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users and roles

yes

Administrators, Users, Groups

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