Dattell

Elastic Stack getting expensive? You’re not imagining it.
Many teams are surprised by the rising costs of enterprise Elastic—between license fees, cloud markups, and bundled features they don’t need.

This post breaks down:

• Where the costs come from
• When it makes sense to switch to third party managed Elasticsearch
• And why OpenSearch is gaining traction

→ Read the full comparison: https://dattell.com/data-architecture-blog/why-is-enterprise-elastic-so-expensive-and-what-are-the-alternatives/

Running Kafka through Confluent? You’re not alone. Many teams are reconsidering Confluent as costs climb—especially when only a fraction of the platform’s features are used.

This post breaks down why some are switching to open-source Apache Kafka with managed support:

• 30–60% cost savings
• No licensing or cloud markups
• Full control with enterprise-grade SLAs

→ Read the breakdown: https://dattell.com/data-architecture-blog/why-teams-are-leaving-confluent-for-open-source-apache-kafka/

Considering Apache Pulsar for your stack? Many teams default to StreamNative for managed Pulsar—but that decision often comes with hidden costs, limited flexibility, and cloud-native messaging that doesn’t hold up under scrutiny.

We break down how Dattell compares:

• Transparent, flat-rate pricing
• Deep Pulsar ops experience
• Real-world clarity on scaling, SLAs, and support
• 99.99% uptime for all engagements, 15-minute response times

→ Read the full comparison: https://dattell.com/data-architecture-blog/comparing-dattell-and-streamnative/

We wrote a guide to help teams evaluate and select the right Kafka service provider by outlining eight critical factors that influence performance, reliability, and long-term value. The guide compares Dattell, Amazon MSK, and Confluent Cloud, highlighting key differences in pricing models, scalability, support, and architecture.

The guide emphasizes the importance of consistent engineering support, recommending providers that assign a dedicated engineer familiar with your systems, rather than rotating staff. It also advises choosing providers that guarantee rapid response times—ideally 15 minutes for production issues—and 99.99% uptime to minimize operational disruptions.

Security is another crucial consideration; the guide suggests deploying Kafka within your own environment to maintain full control over data and compliance, rather than relying on third-party hosting. Additionally, it highlights the value of proactive maintenance and real-time monitoring to identify and resolve issues before they escalate.

For a comprehensive understanding, read the full guide here: https://dattell.com/kafka-service-provider-comparison-guide