DBMS > Amazon Redshift vs. Apache Impala vs. Cloudflare Workers KV vs. GraphDB vs. Infobright

System Properties Comparison Amazon Redshift vs. Apache Impala vs. Cloudflare Workers KV vs. GraphDB vs. Infobright

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Analytic DBMS for Hadoop

A global, low-latency, key-value store for applications on Cloudflare with exceptionally high read volumes and low-latency.

Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

Primary database model

Secondary database models

Document store

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.32
Rank	#283	Overall
	#40	Key-value stores

Score	3.32
Rank	#91	Overall
	#6	Graph DBMS
	#4	RDF stores

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Website

aws.amazon.com/redshift

impala.apache.org

www.cloudflare.com/developer-platform/workers-kv

www.ontotext.com

ignitetech.com/softwarelibrary/infobrightdb

Technical documentation

docs.aws.amazon.com/redshift

impala.apache.org/impala-docs.html

developers.cloudflare.com/kv/api

graphdb.ontotext.com/documentation

Social network pages

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Cloudflare

Ontotext

Ignite Technologies Inc.; formerly InfoBright Inc.

Initial release

2012

2013

2018

2000

2005

Current release

4.1.0, June 2022

10.4, October 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

Some plugins of GraphDB Workbench are open sourced

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

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

C++

Java

Server operating systems

hosted

Linux

hosted

All OS with a Java VM
Linux
OS X
Windows

Linux
Windows

Data scheme

yes

schema-free

schema-free and OWL/RDFS-schema support; RDF shapes

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.

Secondary indexes

restricted

yes

yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes

Knowledge Grid Technology used instead

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL-like DML and DDL statements

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

yes

APIs and other access methods

JDBC
ODBC

HTTP REST
Proprietary protocol

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

ADO.NET
JDBC
ODBC

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Dart
JavaScript
Kotlin
Python
Rust
Scala

.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

in Python

yes

user defined functions and integration of map-reduce

well-defined plugin interfaces; JavaScript server-side extensibility

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Constraint checking

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

fine grained access rights according to SQL-standard

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

More information provided by the system vendor

Specific characteristics

Ontotext GraphDB is a semantic database engine that allows organizations to build...
» more

Competitive advantages

GraphDB allows you to link text and data in big knowledge graphs. It’s easy to experiment...
» more

Typical application scenarios

Metadata enrichment and management, linked data publishing, semantic inferencing...
» more

Key customers

GraphDB provides a platform for building next-generation AI and Knowledge Graph...
» more

Market metrics

GraphDB is the most utilized semantic triplestore for mission-critical enterprise...
» more

Licensing and pricing models

GraphDB Free is a non-commercial version and is free to use. GraphDB Enterprise edition...
» more

News

Integrating GraphDB with Relational Database Systems
23 May 2024

Understanding the Graph Center of Excellence
17 May 2024

Migrating From LPG to RDF Graph Model
8 May 2024

Case study: Policy Enforcement Automation With Semantics
2 May 2024

Okay, RAG… We Have a Problem
26 April 2024

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.