DBMS > AllegroGraph vs. Heroic vs. Kinetica vs. Quasardb vs. Snowflake

System Properties Comparison AllegroGraph vs. Heroic vs. Kinetica vs. Quasardb vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

High performance, persistent RDF store with additional support for Graph DBMS

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Fully vectorized database across both GPUs and CPUs

Distributed, high-performance timeseries database

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

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Secondary database models

Spatial DBMS

Spatial DBMS
Time Series DBMS

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

Score	1.06
Rank	#187	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	0.14
Rank	#332	Overall
	#29	Time Series DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

allegrograph.com

github.com/spotify/heroic

www.kinetica.com

quasar.ai

www.snowflake.com

Technical documentation

franz.com/agraph/support/documentation/current/agraph-introduction.html

spotify.github.io/heroic

docs.kinetica.com

doc.quasar.ai/master

docs.snowflake.net/manuals/index.html

Developer

Franz Inc.

Spotify

Kinetica

quasardb

Snowflake Computing Inc.

Initial release

2004

2014

2012

2009

2014

Current release

8.0, December 2023

7.1, August 2021

3.14.1, January 2024

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

Apache 2.0

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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, C++

C++

Server operating systems

Linux
OS X
Windows

Linux

BSD
Linux
OS X
Windows

hosted

Data scheme

yes

RDF schemas

schema-free

yes

schema-free

yes

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

Typing

predefined data types such as float or date

yes

integer and binary

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.

bulk load of XML files possible

yes

Secondary indexes

yes

via Elasticsearch

yes

with tags

SQL

Support of SQL

SPARQL is used as query language

SQL-like DML and DDL statements

SQL-like query language

yes

APIs and other access methods

RESTful HTTP API
SPARQL

HQL (Heroic Query Language, a JSON-based language)
HTTP API

JDBC
ODBC
RESTful HTTP API

HTTP API

CLI Client
JDBC
ODBC

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

C++
Java
JavaScript (Node.js)
Python

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding

consistent hashing

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

Source-replica replication

Source-replica replication with selectable replication factor

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

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

by using LevelDB

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

GPU vRAM or System RAM

yes

Transient mode

User concepts

Access control

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

Access rights for users and roles on table level

Cryptographically strong user authentication and audit trail

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

More information provided by the system vendor

Specific characteristics

Knowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more

Competitive advantages

AllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more

News

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23 May 2024

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17 April 2024

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3 April 2024

Exploring AllegroGraph v8 – Unleashing the Power of Neuro-Symbolic AI (Recorded Webinar)
9 February 2024

What is Neuro-Symbolic AI?
23 January 2024

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