DBMS > AllegroGraph vs. Amazon Redshift vs. GreptimeDB vs. Ignite

System Properties Comparison AllegroGraph vs. Amazon Redshift vs. GreptimeDB vs. Ignite

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Editorial information provided by DB-Engines

Name

Description

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

Large scale data warehouse service for use with business intelligence tools

An open source Time Series DBMS built for increased scalability, high performance and efficiency

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Relational DBMS

Time Series DBMS

Key-value store
Relational DBMS

Secondary database models

Spatial DBMS

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

Score	1.13
Rank	#179	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#7	Vector DBMS

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.12
Rank	#351	Overall
	#34	Time Series DBMS

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Website

allegrograph.com

aws.amazon.com/redshift

greptime.com

ignite.apache.org

Technical documentation

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

docs.aws.amazon.com/redshift

docs.greptime.com

apacheignite.readme.io/docs

Developer

Franz Inc.

Amazon (based on PostgreSQL)

Greptime Inc.

Apache Software Foundation

Initial release

2004

2012

2022

2015

Current release

8.0, December 2023

Apache Ignite 2.6

License

Commercial or Open Source

commercial

Limited community edition free

commercial

Open Source

Apache Version 2.0

Open Source

Apache 2.0

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

Rust

C++, Java, .Net

Server operating systems

Linux
OS X
Windows

hosted

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

RDF schemas

yes

schema-free, schema definition possible

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.

bulk load of XML files possible

yes

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

SPARQL is used as query language

yes

does not fully support an SQL-standard

yes

ANSI-99 for query and DML statements, subset of DDL

APIs and other access methods

RESTful HTTP API
SPARQL

JDBC
ODBC

gRPC
HTTP API
JDBC

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

All languages supporting JDBC/ODBC

C++
Erlang
Go
Java
JavaScript

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

user defined functions

in Python

Python

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

yes (replicated cache)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

User concepts

Access control

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

fine grained access rights according to SQL-standard

Simple rights management via user accounts

Security Hooks for custom implementations

More information provided by the system vendor

Specific characteristics

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

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Competitive advantages

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

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

News

How a Neuro-Symbolic AI Approach Can Improve Trust in AI Apps
23 May 2024

Can Neuro-Symbolic AI Solve AI’s Weaknesses?
17 April 2024

100 Companies That Matter in KM – Franz Inc.
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.