DBMS > AnzoGraph DB vs. atoti vs. Google Cloud Datastore vs. searchxml

System Properties Comparison AnzoGraph DB vs. atoti vs. Google Cloud Datastore vs. searchxml

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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

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Graph DBMS
RDF store

Object oriented DBMS

Document store

Native XML DBMS
Search engine

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

Score	0.27
Rank	#302	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	0.59
Rank	#242	Overall
	#10	Object oriented DBMS

Score	4.49
Rank	#79	Overall
	#12	Document stores

Score	0.01
Rank	#386	Overall
	#7	Native XML DBMS
	#24	Search engines

Website

cambridgesemantics.com/anzograph

atoti.io

cloud.google.com/datastore

www.searchxml.net/category/products

Technical documentation

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

docs.atoti.io

cloud.google.com/datastore/docs

www.searchxml.net/support/handouts

Developer

Cambridge Semantics

ActiveViam

Google

informationpartners gmbh

Initial release

2018

2008

2015

Current release

2.3, January 2021

1.0

License

Commercial or Open Source

commercial

free trial version available

commercial

free versions available

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.

Implementation language

Java

C++

Server operating systems

Linux

hosted

Windows

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free

Typing

predefined data types such as float or date

yes, details here

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.

Multidimensional Expressions (MDX)

SQL-like query language (GQL)

APIs and other access methods

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

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

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

C++
Java
Python

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

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

user defined functions and aggregates

Python

using Google App Engine

yes

on the application server

Triggers

Callbacks using the Google Apps Engine

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding, horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Multi-source replication using Paxos

yes

sychronisation to multiple collections

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

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

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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)

Domain, group and role-based access control at the document level and for application services

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More resources

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