DBMS > AnzoGraph DB vs. Bangdb vs. Memgraph vs. Snowflake vs. TigerGraph

System Properties Comparison AnzoGraph DB vs. Bangdb vs. Memgraph vs. Snowflake vs. TigerGraph

Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Converged and high performance database for device data, events, time series, document and graph

An open source graph database built for real-time streaming and compatible with Neo4j

Cloud-based data warehousing service for structured and semi-structured data

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Graph DBMS
RDF store

Document store
Graph DBMS
Time Series DBMS

Graph DBMS

Relational DBMS

Graph DBMS

Secondary database models

Spatial DBMS

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

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	3.19
Rank	#94	Overall
	#8	Graph DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

cambridgesemantics.com/anzograph

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

docs.bangdb.com

memgraph.com/docs

docs.snowflake.net/manuals/index.html

docs.tigergraph.com

Social network pages

Developer

Cambridge Semantics

Sachin Sinha, BangDB

Memgraph Ltd

Snowflake Computing Inc.

Initial release

2018

2012

2017

2014

2017

Current release

2.3, January 2021

BangDB 2.0, October 2021

License

Commercial or Open Source

commercial

free trial version available

Open Source

BSD 3

Open Source

BSL 1.1; commercial license for enterprise edition available

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

C and C++

C++

Server operating systems

Linux

hosted

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

schema-free and schema-optional

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

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

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

SQL like support with command line tool

yes

SQL-like query language (GSQL)

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

Proprietary protocol
RESTful HTTP API

Bolt protocol
Cypher query language

CLI Client
JDBC
ODBC

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

C++
Java
Python

C
C#
C++
Java
Python

.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

C++
Java

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

yes

Triggers

yes, Notifications (with Streaming only)

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

Sharding

dynamic graph partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

selectable replication factor, Knob for CAP (enterprise version only)

Multi-source replication using RAFT

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

relationships in graphs

yes

Relationships in graphs

Transaction concepts

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

ACID

with snapshot isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, optimistic concurrency control

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

yes, implements WAL (Write ahead log) as well

yes

with periodic snapshot and write-ahead logging (WAL) of changes

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

yes, run db with in-memory only mode

yes

User concepts

Access control

Access rights for users and roles

yes (enterprise version only)

Users, roles and permissions

Users with fine-grained authorization concept, user roles and pluggable authentication

Role-based access control

More information provided by the system vendor

Specific characteristics

Memgraph directly connects to your streaming infrastructure so you and your team...
» more

Competitive advantages

Business Source License ensures a future for the Memgraph community MAGE algorithm...
» more

Typical application scenarios

Graph algorithms in bioinformatics Social network analysis Cryptocurrency network...
» more

Licensing and pricing models

You can check out our pricing model and licenses on the company website .
» more

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