DBMS > AnzoGraph DB vs. Cachelot.io vs. Google Cloud Datastore vs. SWC-DB vs. Yanza

System Properties Comparison AnzoGraph DB vs. Cachelot.io vs. Google Cloud Datastore vs. SWC-DB vs. Yanza

Editorial information provided by DB-Engines

Name

Yanza seems to be discontinued. 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

In-memory caching system

Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform

A high performance, scalable Wide Column DBMS

Time Series DBMS for IoT Applications

Primary database model

Secondary database models

Time Series DBMS

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Score	4.47
Rank	#76	Overall
	#12	Document stores

Score	0.01
Rank	#376	Overall
	#13	Wide column stores

Website

cambridgesemantics.com/anzograph

cachelot.io

cloud.google.com/datastore

github.com/kashirin-alex/swc-db
www.swcdb.org

yanza.com

Technical documentation

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

cloud.google.com/datastore/docs

Developer

Cambridge Semantics

Google

Alex Kashirin

Yanza

Initial release

2018

2015

2008

2020

2015

Current release

2.3, January 2021

0.5, April 2021

License

Commercial or Open Source

commercial

free trial version available

Open Source

Simplified BSD License

commercial

Open Source

GPL V3

commercial

free version available

Cloud-based only

Only available as a cloud service

yes

but mainly used as a service provided by Yanza

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

C++

Server operating systems

Linux

FreeBSD
Linux
OS X

hosted

Linux

Windows

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

Typing

predefined data types such as float or date

yes, details here

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

SQL

Support of SQL

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

SQL-like query language (GQL)

SQL-like query language

APIs and other access methods

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

Memcached protocol

gRPC (using protocol buffers) API
RESTful HTTP/JSON API

Proprietary protocol
Thrift

HTTP API

Supported programming languages

C++
Java
Python

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
OCaml
Perl
PHP
Python
Ruby

.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++

any language that supports HTTP calls

Server-side scripts

Stored procedures

user defined functions and aggregates

using Google App Engine

Triggers

Callbacks using the Google Apps Engine

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

none

Multi-source replication using Paxos

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

none

Immediate Consistency or Eventual Consistency depending on type of query and configuration

Strong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

via ReferenceProperties or Ancestor paths

Transaction concepts

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

ACID

Serializable Isolation within Transactions, Read Committed outside of Transactions

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources

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AnzoGraph review: A graph database for deep analytics
15 April 2019, InfoWorld

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8 February 2019, Towards Data Science

Back to the future: Does graph database success hang on query language?
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