DBMS > Blazegraph vs. Citus vs. LMDB vs. Microsoft Azure Synapse Analytics vs. Riak KV

System Properties Comparison Blazegraph vs. Citus vs. LMDB vs. Microsoft Azure Synapse Analytics vs. Riak KV

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.

Description

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

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

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

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Distributed, fault tolerant key-value store

Primary database model

with links between data sets and object tags for the creation of secondary indexes

Secondary database models

Document store

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

Score	0.81
Rank	#213	Overall
	#19	Graph DBMS
	#8	RDF stores

Score	2.15
Rank	#117	Overall
	#56	Relational DBMS

Score	2.09
Rank	#121	Overall
	#20	Key-value stores

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	4.01
Rank	#79	Overall
	#9	Key-value stores

Website

blazegraph.com

www.citusdata.com

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

azure.microsoft.com/services/synapse-analytics

Technical documentation

wiki.blazegraph.com

docs.citusdata.com

www.lmdb.tech/doc

docs.microsoft.com/azure/synapse-analytics

www.tiot.jp/riak-docs/riak/kv/latest

Developer

Blazegraph

Symas

Microsoft

OpenSource, formerly Basho Technologies

Initial release

2006

2010

2011

2016

2009

Current release

2.1.5, March 2019

8.1, December 2018

0.9.32, January 2024

3.2.0, December 2022

License

Commercial or Open Source

Open Source

extended commercial license available

Open Source

AGPL, commercial license also available

Open Source

commercial

Open Source

Apache version 2, commercial enterprise edition

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

Java

C++

Erlang

Server operating systems

Linux
OS X
Windows

Linux

Linux
Unix
Windows

hosted

Linux
OS X

Data scheme

schema-free

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.

yes

specific XML type available, but no XML query functionality

Secondary indexes

yes

restricted

SQL

Support of SQL

SPARQL is used as query language

yes

standard, with numerous extensions

yes

APIs and other access methods

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

ADO.NET
JDBC
ODBC

HTTP API
Native Erlang Interface

Supported programming languages

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.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

C#
Java
PHP

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

Server-side scripts

Stored procedures

yes

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

Transact SQL

Erlang

Triggers

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding, horizontal partitioning

Sharding

no "single point of failure"

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

other methods possible by using 3rd party extensions

none

yes

selectable replication factor

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

links between data sets can be stored

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

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

fine grained access rights according to SQL-standard

yes

yes, using Riak Security

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