DBMS > AgensGraph vs. Blazegraph vs. Cassandra vs. Milvus vs. Spark SQL

System Properties Comparison AgensGraph vs. Blazegraph vs. Cassandra vs. Milvus vs. Spark SQL

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

Multi-model database supporting relational and graph data models and built upon PostgreSQL

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

Wide-column store based on ideas of BigTable and DynamoDB

Optimized for write access

A DBMS designed for efficient storage of vector data and vector similarity searches

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

Graph DBMS
Relational DBMS

Secondary database models

Vector DBMS

starting with release V5

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

Score	0.20
Rank	#321	Overall
	#27	Graph DBMS
	#143	Relational DBMS

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

Score	101.89
Rank	#12	Overall
	#1	Wide column stores

Score	2.31
Rank	#113	Overall
	#3	Vector DBMS

Score	18.96
Rank	#33	Overall
	#20	Relational DBMS

Website

bitnine.net/agensgraph

Technical documentation

bitnine.net/documentation

wiki.blazegraph.com

cassandra.apache.org/doc/latest

milvus.io/docs/overview.md

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Bitnine Global Inc.

Blazegraph

Apache Software Foundation

Apache top level project, originally developped by Facebook

Apache Software Foundation

Initial release

2016

2006

2008

2019

2014

Current release

2.1, December 2018

2.1.5, March 2019

4.1.3, July 2023

2.3.4, January 2024

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

Apache License 2.0

Open Source

extended commercial license available

Open Source

Apache version 2

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Zilliz Cloud – Cloud-native service for Milvus

Implementation language

Java

C++, Go

Scala

Server operating systems

Linux
OS X
Windows

BSD
Linux
OS X
Windows

Linux
macOS

10.14 or later
Windows

with WSL 2 enabled

Linux
OS X
Windows

Data scheme

depending on used data model

schema-free

yes

Typing

predefined data types such as float or date

yes

RDF literal types

yes

Vector, Numeric and String

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

restricted

only equality queries, not always the best performing solution

SQL

Support of SQL

yes

SPARQL is used as query language

SQL-like SELECT, DML and DDL statements (CQL)

SQL-like DML and DDL statements

APIs and other access methods

Cypher Query Language
JDBC

Java API
RESTful HTTP API
SPARQL QUERY
SPARQL UPDATE
TinkerPop 3

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

RESTful HTTP API

JDBC
ODBC

Supported programming languages

C
Java
JavaScript
Python

.Net
C
C++
Java
JavaScript
PHP
Python
Ruby

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

C++
Go
Java
JavaScript (Node.js)
Python

Java
Python
R
Scala

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding

no "single point of failure"

Sharding

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

selectable replication factor

Representation of geographical distribution of servers is possible

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Bounded Staleness
Eventual Consistency
Immediate Consistency
Session Consistency
Tunable Consistency

Foreign keys

Referential integrity

yes

Relationships in Graphs

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

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)

Access rights for users can be defined per object

Role based access control and fine grained access rights

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

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Licensing and pricing models

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