DBMS > Amazon SimpleDB vs. BigchainDB vs. DolphinDB vs. Ingres vs. SQLite

System Properties Comparison Amazon SimpleDB vs. BigchainDB vs. DolphinDB vs. Ingres vs. SQLite

Editorial information provided by DB-Engines

Name

Description

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

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.

Well established RDBMS

Widely used embeddable, in-process RDBMS

Primary database model

Key-value store

Document store

Time Series DBMS
Vector DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	1.89
Rank	#128	Overall
	#22	Key-value stores

Score	0.76
Rank	#216	Overall
	#36	Document stores

Score	2.72
Rank	#100	Overall
	#8	Time Series DBMS
	#5	Vector DBMS

Score	3.63
Rank	#79	Overall
	#43	Relational DBMS

Score	103.35
Rank	#10	Overall
	#7	Relational DBMS

Website

aws.amazon.com/simpledb

www.bigchaindb.com

www.dolphindb.com

www.actian.com/databases/ingres

www.sqlite.org

Technical documentation

docs.aws.amazon.com/simpledb

bigchaindb.readthedocs.io/en/latest

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

docs.actian.com/ingres

www.sqlite.org/docs.html

Developer

Amazon

DolphinDB, Inc

Actian Corporation

Dwayne Richard Hipp

Initial release

2007

2016

2018

1974

originally developed at University Berkely in early 1970s

2000

Current release

v2.00.4, January 2022

12.0, July 2024

3.46.1 (13 August 2024), August 2024

License

Commercial or Open Source

commercial

Open Source

AGPL v3

commercial

free community version available

commercial

Open Source

Public Domain

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

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

server-less

Data scheme

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

not rigid because of 'dynamic typing' concept.

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

yes

All columns are indexed automatically

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

RESTful HTTP API

CLI Client
RESTful HTTP API

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

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

Go
Haskell
Java
JavaScript
Python
Ruby

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding must be implemented in the application

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes

Ingres Replicator

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Concurrent data updates can be detected by the application

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

via file-system locks

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 can be defined via the AWS Identity and Access Management (IAM)

yes

Administrators, Users, Groups

fine grained access rights according to SQL-standard

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