Ease of use (compared to other semantic web stack solutions). Degree of inferencing implementation.

Over the last years, GraphDB has improved a lot, speaking about performance and inference.

While not impossible it is rather awkward though.

Solution for transforming relational data into RDF with OpenRefine integration. Query performance (for SELECT, a evaluation for INSERT queries could not be given due to use of free version).

The User interface is quite nice, and appealing. The blogs are well written and very informative, and is a good means to keep customers updated with the latest developments in the area of semantics.

We've had a really good time working with it. Once we have a good model definition (which applies for any graph engine) it simply works and works really well.

Graph database are poor at aggregating data,Don't use it for Business Intelligence. It is difficult to implement versioning/auditing of data in a graph database.

Visualization of the graph does not work, at least not with the settings I tried (no inference).

I can be very short about my (our) experiences so far with GraphDB. GraphDB is a clear winner for our usecases now.

The webservice api allows manipulation of the repositories (create, delete, import). The only problem is that after some updates, the speed of the endpoint queries dorps very much.

I Like this product because is easy to start, it has a REST api and UI simple to use.

Simplicty i liked unlike SQL Databases where relationship becomes so complex and then you Normalize. Being Simple, we can easily handle objects in very easy way.

OntoRefine is a great way of moving tabular data in triples. The APIs are very well designed, Customer service and technical support is excellent.

Graph DB has been always the most performant one. Another feature that I loved from it is that, in order to install it, you simply copy a single jar file and you're almost ready to go.

Good performance, a lot of features, great UI and documentation, ease of administration and use.

It might be tricky and time taking to deploy a Redis cluster.

However, good planning is necessary to ensure synchronization between the SQL database and REDIS. In addition to a good maturity to map data from one database to another.

Redis is widely being used for in-memory -cache and distributed cache management. It is having good CLI which facilitates easy administration.

It is a difficult task to learn how to use Redis from the documentation.

Our experience was great, we were able to accomplish our goals and the support team was more than generous with there time.

This cache we can use in temporary data storage, page caching etc. I like redis high speed cache, reliability and it is easy to use. It can help to build faster application with fast performance.

The web-UI for managing and interacting with your databases is fairly confusing.

It's fast, reliable, and easy to use. The added support and scalability of Redis Enterprise allows an already easy to use solution to scale to solve any problem.

It is fairly simple to get up and running and extremely cost effective. Beyond those base points, it scales extremely well and performance is great.

Supports complex types of values. It is Possible to build an architecture with high availability.

I liked the simplicity of creating and retrieving keys and the integrations available with different programming languages.

I have participated in the choice of Redis to implement a in-memory cache. I consider Redis a very good choice in the field of databases, and the best of its kind (inmemory database).

Its a great piece of software with great ease of usage.

Good database for storing data and supporting data structures.

My favorite feature is that it has a very flexible and performance oriented structure. It is a cache management application that is already used all over the world and has a large community.

The overall experience has been good. We use it for storing/accessing user sessions and it has met our needs very well with little cost.

To accomplish such excellent efficiency, Redis has some constraints on how it displays its information. For something that operates as quickly as Redis, this trade off is often worth it.

The ease of use of the tool makes it amazing and very useful.

From initial experience onward, still an excellent in-memory database.

Redis Enterprise is a good fit for large implementations which require support.

We have used redis extensively primarily because of friendly UI design. It is so easy to integrate and running in the organization.

Takes a bit of time to get it up and running. Had trouble when trying to setup on one of the website we were making but ended working out.

Being a non-SQL database, it does not require any structure. Perfect for unstructured data like key-value pairs.

Redis has a very good query API, and they are in their website each operation is clearly mentioned with its time complexity. This gives you a clear picture of performance.

I like most the structure and the performances obtained during this product utilization.

The fact that Redis boasts of more than a billion downloads means that if you have a problem you are most likely not the first person to come across it.

The Redis does very well what is proposed to be done, there is nothing that I think is bad about it.

For a beginner, it might be tough to know about its all functionality. Somehow I feel the pricing is also one more reason.

Its easy to use solution. I am overall happy with performance and integration of this solution.

The interface is  well organized and easy to navigate. Scheduling automated backups is intuitive and saves a lot of time.

Redis Enterprise provides a managed solution which is deployed on memory-optimized instances for the best performance.

These ready solutions and new data structures are helping to build software applications much faster and with great performances.

I like most about open source redis is how quickly it's growing and with seamless service support.

US Dollar

GraphDB is a database management solution that helps businesses in finance, publishing, healthcare and other industries create knowledge graphs and streamline data indexing operations. The built-in NoSQL database system allows IT teams to manage storage and retrieval of data from relational databases.


The platform enables employees to parse structured data in JSON, XML, CSV, XLS and other formats and perform semantic searches in real-time. Features of GraphDB include data storage management, reporting, semantic tagging, data visualization and more. Additionally, it lets IT professionals generate and store the resource description framework (RDF) data in a centralized repository.


GraphDB facilitates integration with a document-based database system, MongoDB, which enables users to automate the database querying processes. Pricing is available on request and support is extended via phone, email and a knowledge base.



LongDescription

User Management

Data Verification

Database Support

Access Controls/Permissions

Data Storage Management

Data Synchronization

SSL Security

Semantic Search

Graph Database

Data Capture and Transfer

Full Text Search

Data Import/Export

NOSQL Database Management

Performance Testing

Real Time Data

Data Retrieval

Data Connectors

Role-Based Permissions

Data Virtualization

Activity Dashboard

Data Visualization

Multiple Data Sources

Authentication

Performance Analysis

Data Recovery

Monitoring

Backup and Recovery

Secure Data Storage

Data Replication

Third-Party Integrations

Indexing

Data Mapping

Search/Filter

Windows 7

Windows Vista

Windows XP

Mac OS

Linux

Windows 8

Windows 10

GraphDB offers a 60-day free trial for new users, after which the software is available across 3 pricing tiers - GraphDB Enterprise, GraphDB Standard, and GraphDB Free on a perpetual license basis. Please contact Ontotext directly for pricing information.

Email/Help Desk

FAQs/Forum

Knowledge Base

Phone Support

Chat

Self-Employed

2-10

11-50

51-200

201-500

501-1000

1000+

GraphDB

In Person

Live Online

Webinars

Documentation

Videos

Redis Enterprise is a cloud-based and on-premise database management software that helps businesses handle operations related to automatic failover management, data processing, caching, data persistence, and more on a centralized platform. It enables staff members to manage in-memory replication, periodic data backups, and auto-cluster recovery processes.

Redis Enterprise allows supervisors to explore several data-structures or data-models, analyze memory usage, and monitor commands in real-time. It provides local read and write latency across multiple clouds and geographical locations and failovers between regions, clouds, and hybrid deployments. The platform is built with JSON, Streams, TimeSeries, Graph and BloomFilter, providing employees with extensive indexing and search capabilities. It also lets team members manage auto-scaling, re-sharding, and rebalancing operations from within a unified portal.

Redis Enterprise offers an API, which lets businesses integrate the platform with several third-party solutions. Administrators can set up role-based access rights, maintain system logs, configure SSL-based authentication, and generate usage reports to ensure a secure user experience.

Real-Time Monitoring

Mobile Access

Data Dictionary Management

Object Oriented Database

For NoSQL Databases

Multiple Programming Languages Supported

Automatic Backup

Reporting/Analytics

Data Migration

Database Conversion

Web browser (OS agnostic)

Redis Enterprise Cloud offers a 30MB free tier and subsequent pricing is based on throughput and dataset requirements, outlined below. 
Essentials: Starting at $5/month (100MB and 4 datasets)
Pro (High Throughput): Starting at $1.94/hour (100k ops/sec, 10GB and 64 databases)
Pro (Large Datasets): Starting at $2.92/hour (50k ops/sec, 50GB and 32 datasets)
Pro (Very Large Datasets): Starting at $4.12/hour (10k ops/sec, 200GB and 2 datasets)

Redis Enterprise Software (on-premise) offers a 30 days free trial and further pricing information is available on request.

GraphDB vs Redis Enterprise

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