DBMS > AnzoGraph DB vs. Realm vs. Snowflake vs. Transwarp KunDB

System Properties Comparison AnzoGraph DB vs. Realm vs. Snowflake vs. Transwarp KunDB

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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

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

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

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

Graph DBMS
RDF store

Document store

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	7.41
Rank	#52	Overall
	#8	Document stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.14
Rank	#341	Overall
	#149	Relational DBMS

Website

cambridgesemantics.com/anzograph

realm.io

www.snowflake.com

www.transwarp.cn/en/product/kundb

Technical documentation

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

realm.io/docs

docs.snowflake.net/manuals/index.html

Developer

Cambridge Semantics

Realm, acquired by MongoDB in May 2019

Snowflake Computing Inc.

Transwarp

Initial release

2018

2014

Current release

2.3, January 2021

License

Commercial or Open Source

commercial

free trial version available

Open Source

commercial

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.

Server operating systems

Linux

Android
Backend: server-less
iOS
Windows

hosted

Data scheme

Schema-free and OWL/RDFS-schema support

yes

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

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

APIs and other access methods

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

CLI Client
JDBC
ODBC

Supported programming languages

C++
Java
Python

.Net
Java

with Android only
Objective-C
React Native
Swift

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

runs within the applications so server-side scripts are unnecessary

user defined functions

yes

Triggers

yes

Change Listeners

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

yes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

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

In-Memory realm

User concepts

Access control

Access rights for users and roles

yes

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

yes

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