DBMS > Amazon Redshift vs. Blazegraph vs. Drizzle vs. LMDB

System Properties Comparison Amazon Redshift vs. Blazegraph vs. Drizzle vs. LMDB

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Editorial information provided by DB-Engines

Name

Amazon has acquired Blazegraph's domain and (probably) product. It is said that Amazon Neptune is based on Blazegraph.

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

Description

Large scale data warehouse service for use with business intelligence tools

High-performance graph database supporting Semantic Web (RDF/SPARQL) and Graph Database (tinkerpop3, blueprints, vertex-centric) APIs with scale-out and High Availability.

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

A high performant, light-weight, embedded key-value database library

Primary database model

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.75
Rank	#219	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	1.99
Rank	#125	Overall
	#21	Key-value stores

Website

aws.amazon.com/redshift

blazegraph.com

www.symas.com/symas-embedded-database-lmdb

Technical documentation

docs.aws.amazon.com/redshift

wiki.blazegraph.com

www.lmdb.tech/doc

Developer

Amazon (based on PostgreSQL)

Blazegraph

Drizzle project, originally started by Brian Aker

Symas

Initial release

2012

2006

2008

2011

Current release

2.1.5, March 2019

7.2.4, September 2012

0.9.32, January 2024

License

Commercial or Open Source

commercial

Open Source

extended commercial license available

Open Source

GNU GPL

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

hosted

Linux
OS X
Windows

FreeBSD
Linux
OS X

Linux
Unix
Windows

Data scheme

yes

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

RDF literal types

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SPARQL is used as query language

yes

with proprietary extensions

APIs and other access methods

JDBC
ODBC

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

JDBC

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

C
C++
Java
PHP

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Triggers

hooks for callbacks inside the server can be used.

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Relationships in Graphs

yes

Transaction concepts

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

ACID

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

User concepts

Access control

fine grained access rights according to SQL-standard

Security and Authentication via Web Application Container (Tomcat, Jetty)

Pluggable authentication mechanisms

e.g. LDAP, HTTP

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