DBMS > AnzoGraph DB vs. atoti vs. Valentina Server vs. Warp 10

System Properties Comparison AnzoGraph DB vs. atoti vs. Valentina Server vs. Warp 10

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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.

Object-relational database and reports server

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

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	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	0.21
Rank	#325	Overall
	#144	Relational DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

cambridgesemantics.com/anzograph

atoti.io

www.valentina-db.net

www.warp10.io

Technical documentation

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

docs.atoti.io

valentina-db.com/docs/dokuwiki/v5/doku.php

www.warp10.io/content/02_Getting_started

Developer

Cambridge Semantics

ActiveViam

Paradigma Software

SenX

Initial release

2018

1999

2015

Current release

2.3, January 2021

5.7.5

License

Commercial or Open Source

commercial

free trial version available

commercial

free versions available

commercial

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java

Server operating systems

Linux

Linux
OS X
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

yes

schema-free

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.

Secondary indexes

yes

SQL

Support of SQL

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

Multidimensional Expressions (MDX)

yes

APIs and other access methods

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

ODBC

HTTP API
Jupyter
WebSocket

Supported programming languages

C++
Java
Python

.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET

Server-side scripts

Stored procedures

user defined functions and aggregates

Python

yes

WarpScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding, horizontal partitioning

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

selectable replication factor

based on HBase

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

based on HBase

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

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

fine grained access rights according to SQL-standard

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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More resources

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