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Description
Terracotta DB offers a robust, distributed solution for in-memory data management, addressing both caching and operational storage needs while facilitating both transactional and analytical processes. The combination of swift RAM capabilities with extensive data resources empowers businesses significantly. With BigMemory, users benefit from: immediate access to vast amounts of in-memory data, impressive throughput paired with consistently low latency, compatibility with Java®, Microsoft® .NET/C#, and C++ applications, and an outstanding 99.999% uptime. The system boasts linear scalability, ensuring data consistency across various servers, and employs optimized data storage strategies across both RAM and SSDs. Additionally, it provides SQL support for in-memory data queries, lowers infrastructure expenses through enhanced hardware efficiency, and guarantees high-performance, persistent storage that ensures durability and rapid restarts. Comprehensive monitoring, management, and control features are included, alongside ultra-fast data stores that intelligently relocate data as needed. Furthermore, the capacity for data replication across multiple data centers enhances disaster recovery capabilities, enabling real-time management of dynamic data flows. This suite of features positions Terracotta DB as an essential asset for enterprises striving for efficiency and reliability in their data operations.
Description
Voldemort does not function as a relational database, as it does not aim to fulfill arbitrary relations while adhering to ACID properties. It also does not operate as an object database that seeks to seamlessly map object reference structures. Additionally, it does not introduce a novel abstraction like document orientation. Essentially, it serves as a large, distributed, durable, and fault-tolerant hash table. For applications leveraging an Object-Relational (O/R) mapper such as ActiveRecord or Hibernate, this can lead to improved horizontal scalability and significantly enhanced availability, albeit with a considerable trade-off in convenience. In the context of extensive applications facing the demands of internet-level scalability, a system is often comprised of multiple functionally divided services or APIs, which may handle storage across various data centers with their own horizontally partitioned storage systems. In these scenarios, the possibility of performing arbitrary joins within the database becomes impractical, as not all data can be accessed within a single database instance, making data management even more complex. Consequently, developers must adapt their strategies to navigate these limitations effectively.
API Access
Has API
API Access
Has API
Integrations
FF4J
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
Software AG
Founded
1969
Country
Germany
Website
www.softwareag.com
Vendor Details
Company Name
Voldemort
Website
www.project-voldemort.com/voldemort/
Product Features
Data Management
Customer Data
Data Analysis
Data Capture
Data Integration
Data Migration
Data Quality Control
Data Security
Information Governance
Master Data Management
Match & Merge
Product Features
Data Replication
Asynchronous Data Replication
Automated Data Retention
Continuous Replication
Cross-Platform Replication
Dashboard
Instant Failover
Orchestration
Remote Database Replication
Reporting / Analytics
Simulation / Testing
Synchronous Data Replication
