DBMS > AnzoGraph DB vs. Snowflake vs. SurrealDB vs. Trafodion

System Properties Comparison AnzoGraph DB vs. Snowflake vs. SurrealDB vs. Trafodion

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Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

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

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

A fully ACID transactional, developer-friendly, multi-model DBMS

Transactional SQL-on-Hadoop DBMS

Primary database model

Graph DBMS
RDF store

Relational DBMS

Document store
Graph DBMS

Relational 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	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	1.02
Rank	#190	Overall
	#33	Document stores
	#18	Graph DBMS

Website

cambridgesemantics.com/anzograph

www.snowflake.com

surrealdb.com

trafodion.apache.org

Technical documentation

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

docs.snowflake.net/manuals/index.html

surrealdb.com/docs

trafodion.apache.org/documentation.html

Developer

Cambridge Semantics

Snowflake Computing Inc.

SurrealDB Ltd

Apache Software Foundation, originally developed by HP

Initial release

2018

2014

2022

2014

Current release

2.3, January 2021

v1.5.0, May 2024

2.3.0, February 2019

License

Commercial or Open Source

commercial

free trial version available

commercial

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Rust

C++, Java

Server operating systems

Linux

hosted

Linux
macOS
Windows

Linux

Data scheme

Schema-free and OWL/RDFS-schema support

yes

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

schema-free

yes

Typing

predefined data types such as float or date

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

SQL

Support of SQL

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

yes

SQL-like query language

yes

APIs and other access methods

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

CLI Client
JDBC
ODBC

GraphQL
RESTful HTTP API
WebSocket

ADO.NET
JDBC
ODBC

Supported programming languages

C++
Java
Python

JavaScript (Node.js)
Python

Deno
Go
JavaScript (Node.js)
Rust

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

Java Stored Procedures

Triggers

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

yes

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Foreign keys

Referential integrity

not needed 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

Access rights for users and roles

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

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

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