RaimaDB
4.8 out of 5 starsRatings and Reviews 12 Ratings
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What is RaimaDB?
RaimaDB is an embedded time series database designed specifically for Edge and IoT devices, capable of operating entirely in-memory. This powerful and lightweight relational database management system (RDBMS) is not only secure but has also been validated by over 20,000 developers globally, with deployments exceeding 25 million instances. It excels in high-performance environments and is tailored for critical applications across various sectors, particularly in edge computing and IoT. Its efficient architecture makes it particularly suitable for systems with limited resources, offering both in-memory and persistent storage capabilities. RaimaDB supports versatile data modeling, accommodating traditional relational approaches alongside direct relationships via network model sets. The database guarantees data integrity with ACID-compliant transactions and employs a variety of advanced indexing techniques, including B+Tree, Hash Table, R-Tree, and AVL-Tree, to enhance data accessibility and reliability. Furthermore, it is designed to handle real-time processing demands, featuring multi-version concurrency control (MVCC) and snapshot isolation, which collectively position it as a dependable choice for applications where both speed and stability are essential. This combination of features makes RaimaDB an invaluable asset for developers looking to optimize performance in their applications.
What is Heroic?
Heroic is an open-source monitoring tool that was originally crafted at Spotify to address difficulties associated with the vast-scale gathering and near real-time evaluation of metrics. It consists of a small set of specialized components, each designed for specific functions within the system. Heroic provides unlimited data retention, provided there is sufficient investment in hardware, as well as federation capabilities that allow multiple Heroic clusters to interconnect and offer a cohesive interface. A pivotal feature, known as Consumers, is responsible for the ingestion of metrics, showcasing the system's emphasis on operational efficiency. Throughout Heroic's development, it became clear that overseeing hundreds of millions of time series without adequate context presents notable hurdles. Furthermore, the federation support enhances the system's ability to manage requests across different independent Heroic clusters, enabling them to deliver services to clients through a single, global interface. This not only optimizes operations but also reduces cross-regional traffic, as each cluster can operate autonomously within its specific area. As a result, Heroic stands out as a powerful solution for organizations seeking effective monitoring tools, capable of adapting to diverse operational needs. The combination of these features makes Heroic a compelling choice for enterprises aiming for scalable and efficient monitoring capabilities.
Integrations Supported
BlackBerry QNX
Embedded Linux
FreeRTOS
INTEGRITY RTOS
QNX Neutrino RTOS
SymmetricDS
Integrations Supported
Apache Cassandra
Apache Kafka
Elasticsearch
Google Cloud Bigtable
API Availability
API Availability
Has API
Pricing Information
Pricing not provided
Free Trial Offered?
Pricing Information
Pricing not provided
Supported Platforms
Android
iPhone
iPad
Windows
Mac
Linux
Supported Platforms
SaaS
Customer Service / Support
Standard Support
24 Hour Support
Web-Based Support
Customer Service / Support
Web-Based Support
Training Options
Documentation Hub
Webinars
Online Training
On-Site Training
Training Options
Documentation Hub
Company Facts
Organization Name
Raima
Date Founded
1984
Company Location
United States
Company Website
raima.com
Company Facts
Organization Name
Heroic
Company Website
spotify.github.io/heroic
Categories and Features
Big Data
Not specified
Data Management
Not specified
Data Replication
Not specified
Database
Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Database Conversion
Mobile Access
Monitoring
Performance Analysis
Queries
Relational Interface
Database Management Systems (DBMS)
Not specified
Embedded Database
Not specified
In-Memory Databases
Not specified
IoT
Application Development
Big Data Analytics
Configuration Management
Connectivity Management
Data Collection
Data Management
Device Management
Performance Management
Prototyping
RDBMS
Backup
Data Migration
Monitoring
Performance Analysis
Queries
Storage Optimization
Real-Time Analytic Databases
Not specified
Relational Database
ACID Compliance
Data Failure Recovery
Multi-Platform
Referential Integrity
SQL DDL Support
SQL DML Support
System Catalog
Unicode Support
SQL Databases
Not specified
SQL Server
Not specified
Time Series Databases
Not specified
Categories and Features
Time Series Databases
Not specified