Average Ratings 0 Ratings
Average Ratings 0 Ratings
Description
Diom serves as a comprehensive platform for backend components that facilitates the creation of resilient services, providing a suite of seamlessly integrated infrastructure tools tailored for backend and data engineers, such as caching, key-value storage, rate-limiting, idempotency, queues, and streams. This platform is crafted to eliminate the need for engineers to construct fragile, slow, and cumbersome solutions atop systems like Redis, Postgres, or other data stores, enabling them to instead benefit from powerful, efficient, and thoroughly tested components designed for prevalent backend patterns. By utilizing Diom, organizations can consolidate multiple services, including Redis, RabbitMQ, and Kafka, for various applications, leading to a significant reduction in service dependencies, operational complexity, monitoring demands, backup requirements, configuration efforts, and overall deployment expenses. Its components are optimized for low-latency performance, feature minimal round-trip times, provide HTTP-based APIs, and come with SDKs for widely-used programming languages, all while being deployable in standard backend environments. Additionally, Diom’s cohesive architecture ensures that engineers can focus more on innovation rather than maintenance, thus enhancing overall productivity.
Description
Redis Enterprise offers a robust real-time indexing, querying, and full-text search engine that is accessible both on-premises and as a cloud-managed service. This real-time search capability is optimized for rapid indexing and data ingestion, utilizing high-performance in-memory data structures developed in C. You can expand and partition indexes across multiple shards and nodes, enhancing both speed and memory capacity. With an impressive five-nines availability and Active-Active failover, uninterrupted operations are ensured in any circumstance. The real-time search feature of Redis Enterprise enables users to swiftly establish primary and secondary indexes on Hash and JSON datasets through an incremental indexing method, which facilitates quick index creation and removal. These indexes empower users to perform queries at remarkable speeds, execute complex aggregations, and filter data based on properties, numeric ranges, and geographical distances, thus enhancing overall data accessibility. By leveraging these capabilities, organizations can significantly improve their data management and retrieval processes.
API Access
Has API
API Access
Has API
Integrations
Redis
Acontext
Apache Kafka
Archon Data Store
Camunda
Go
Java
Lygos
PostgreSQL
Python
Integrations
Redis
Acontext
Apache Kafka
Archon Data Store
Camunda
Go
Java
Lygos
PostgreSQL
Python
Pricing Details
No price information available.
Free Trial
Free Version
Pricing Details
No price information available.
Free Trial
Free Version
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Deployment
Web-Based
On-Premises
iPhone App
iPad App
Android App
Windows
Mac
Linux
Chromebook
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Customer Support
Business Hours
Live Rep (24/7)
Online Support
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Types of Training
Training Docs
Webinars
Live Training (Online)
In Person
Vendor Details
Company Name
Svix
Founded
2021
Country
United States
Website
diom.svix.com
Vendor Details
Company Name
Redis
Country
United States
Website
redis.com/modules/redis-search/
Product Features
Product Features
Enterprise Search
AI / Machine Learning
Faceted Search / Filtering
Full Text Search
Fuzzy Search
Indexing
Text Analytics
eDiscovery