DBMS > Amazon DynamoDB vs. Hyprcubd vs. LevelDB vs. OrigoDB vs. SQLite

System Properties Comparison Amazon DynamoDB vs. Hyprcubd vs. LevelDB vs. OrigoDB vs. SQLite

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

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

Serverless Time Series DBMS

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

A fully ACID in-memory object graph database

Widely used embeddable, in-process RDBMS

Primary database model

Document store
Key-value store

Time Series DBMS

Key-value store

Document store
Object oriented DBMS

Relational 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	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

aws.amazon.com/dynamodb

hyprcubd.com (offline)

github.com/google/leveldb

origodb.com

www.sqlite.org

Technical documentation

docs.aws.amazon.com/dynamodb

github.com/google/leveldb/blob/main/doc/index.md

origodb.com/docs

www.sqlite.org/docs.html

Developer

Amazon

Hyprcubd, Inc.

Google

Robert Friberg et al

Dwayne Richard Hipp

Initial release

2012

2011

2009

under the name LiveDB

2000

Current release

1.23, February 2021

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

commercial

free tier for a limited amount of database operations

commercial

Open Source

BSD

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

C++

Server operating systems

hosted

Illumos
Linux
OS X
Windows

Linux
Windows

server-less

Data scheme

schema-free

yes

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

RESTful HTTP API

gRPC (https)

.NET Client API
HTTP API
LINQ

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

.Net
ColdFusion
Erlang
Groovy
Java
JavaScript
Perl
PHP
Python
Ruby

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net

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

by integration with AWS Lambda

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be specified for read operations

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

depending on model

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

Write ahead log

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)

token access

Role based authorization

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