Find out what your peers are saying about Microsoft, MongoDB, Redis and others in NoSQL Databases.
Getting an MVP of that project would have taken six to eight months, but because we had an active choice of using Azure Cosmos DB and other related cloud-native services of Azure, we were able to get to an MVP stage in a matter of weeks, which is six weeks.
You can react quickly and trim down the specs, memory, RAM, storage size, etc. It can save about 20% of the costs.
When I have done comparisons or cost calculations, I have sometimes personally seen as much as 25% to 30% savings.
Technical support is very costly for me, accounting for twenty-five to thirty percent of the product cost.
Premier Support has deteriorated compared to what it used to be, especially for small to medium-sized customers like ours.
The response was quick.
I would rate customer service and support a nine out of ten.
It is provided as a pre-configured box, and scaling is not an option.
The system scales up capacity when needed and scales down when not in use, preventing unnecessary expenses.
We like that it can auto-scale to demand, ensuring we only pay for what we use.
We have had no issues with its ability to search through large amounts of data.
We have multiple availability zones, so nothing goes down.
Azure Cosmos DB would be a good choice if you have to deploy your application in a limited time frame and you want to auto-scale the database across different applications.
I would rate it a ten out of ten in terms of availability and latency.
The cloud version is only available in AWS, and in the Middle East, it is not well-developed in the Azure environment.
We must ensure data security remains the top priority.
You have to monitor the Request Units.
The dashboard could include more detailed RU descriptions, IOPS, and compute metrics.
Initially, it seemed like an expensive way to manage a NoSQL data store, but so many improvements that have been made to the platform have made it cost-effective.
Cosmos DB is expensive, and the RU-based pricing model is confusing.
Cosmos DB is great compared to other databases because we can reduce the cost while doing the same things.
It operates as a high-speed data warehouse, which is essential for handling big data.
The most valuable feature of Microsoft Azure Cosmos DB is its real-time analytics capabilities, which allow for turnaround times in milliseconds.
Performance and security are valuable features, particularly when using Cosmos DB for MongoDB emulation and NoSQL.
The performance and scaling capabilities of Cosmos DB are excellent, allowing it to handle large workloads compared to other services such as Azure AI Search.
| Company Size | Count |
|---|---|
| Small Business | 9 |
| Midsize Enterprise | 6 |
| Large Enterprise | 33 |
| Company Size | Count |
|---|---|
| Small Business | 33 |
| Midsize Enterprise | 24 |
| Large Enterprise | 58 |
IBM Netezza Performance Server offers high performance, scalability, and minimal maintenance. It seamlessly integrates SQL for efficient data processing, making it ideal for enterprise data warehousing needs.
IBM Netezza Performance Server is known for its outstanding data processing capabilities. Its integration of FPGA technology, compression techniques, and partitioning optimizes query execution and scalability. Users appreciate its appliance-like architecture for straightforward deployment, distributed querying, and high availability, significantly boosting operations and analytics capabilities. However, there are areas for improvement, particularly in handling high concurrency, real-time integration, and specific big data functionalities. Enhancements in database management tools, XML integration, and cloud options are commonly desired, along with better marketing and community engagement.
What are the key features of IBM Netezza Performance Server?Industries rely on IBM Netezza Performance Server for robust data warehousing solutions, particularly in sectors requiring intensive data analysis such as finance, retail, and telecommunications. Organizations use it to power business intelligence tools like Business Objects and MicroStrategy for customer analytics, establishing data marts and staging tables to efficiently manage and update enterprise data. With the capacity to handle large volumes of compressed and uncompressed data, it finds numerous applications in on-premises setups, powering data mining and reporting with high reliability and efficiency.
Microsoft Azure Cosmos DB offers scalable, geo-replicated, multi-model support with high performance and low latency. It provides seamless Microsoft service integration, benefiting those needing flexible NoSQL, real-time analytics, and automatic scaling for diverse data types and quick global access.
Azure Cosmos DB is designed to store, manage, and query large volumes of both unstructured and structured data. Its NoSQL capabilities and global distribution are leveraged by organizations to support activities like IoT data management, business intelligence, and backend databases for web and mobile applications. While its robust security measures and availability are strengths, there are areas for improvement such as query complexity, integration with services like Databricks and MongoDB, documentation clarity, and performance issues. Enhancements in real-time analytics, API compatibility, cross-container joins, and indexing capabilities are sought after. Cost management, optimization tools, and better support for local development also require attention, as do improvements in user interface and advanced AI integration.
What are the key features of Azure Cosmos DB?Industries use Azure Cosmos DB to support business intelligence and IoT data management, using its capabilities for backend databases in web and mobile applications. The platform's scalability and real-time analytics benefit sectors like finance, healthcare, and retail, where managing diverse datasets efficiently is critical.
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