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Fixing Kafka’s 80% problem with a serious fully managed free Kafka.

We benchmarked Diskless Kafka (KIP-1150) with 1 GiB/s in, 3 GiB/s out workload across three AZs. The cluster ran on just six m8g.4xlarge machines, sitting at <30% CPU, delivering ~1.6 seconds P99 end-to-end latency - all while cutting infra spend from ≈$3.32 M a year to under $288k a year. That’s a >94% cloud cost reduction. Extending Apache Kafka does come with an explicit tax.

When it comes to text search, PostgreSQL offers a surprisingly rich set of tools. Initially, text search capabilities were quite basic, often relying on the LIKE operator. This is inefficient for large amounts of text and lacks the nuance that comes with language. A major breakthrough came with the introduction of the built-in tsquery and tsvector data types, along with the associated functions, as part of PostgreSQL's core distribution. But tsquery is not the only option.

For ClickHouse to achieve the speed it's known for, it has historically relied on a trigger-based and incremental architecture for materialized views. This architecture is known to be very efficient but lacks flexibility, such as when working with data that needs to be backfilled rather than append-only.

We’ve all built the standard RAG pipeline: chunk data, embed it, store it, retrieve it. It works… maybe. Just like LLMs have added a thinking mode for better results, we can add a bit of thinking to our RAG pipelines with agentic RAG using PostgreSQL and n8n.

Aiven is introducing a new pricing plan for Aiven for PostgreSQL services. Starting at $8 USD per month, the Developer tier offers more storage, so you can scale up your free PostgreSQL service in a cost-effective way. Unlike the Free tier, services on the Developer tier are not automatically powered off if inactive. The Developer tier also automatically includes Basic support services. More information on the Developer tier is available in the Aiven docs.

For years, PostgreSQL relied on synchronous I/O, meaning that when the database needed data from disk, each read operation was a blocking system call. The database process would therefore pause and wait for the data retrieval before moving to the next task. Synchronous I/O works well for local storage, but our database needs have changed drastically since then, resulting in this architecture creating significant bottlenecks when storage has higher latency.

Do you like working with time in your code? If yes, you’re likely one of the lucky ones who are blissfully unaware of how deep the rabbit hole goes. If you don’t like it, I have good news for you! Postgres can make working with time more enjoyable! The newly released temporal constraints let you easily maintain referential integrity across temporal relationships. That might seem simple, but it's kind of a big deal. Let’s explore it through an example.

Discover the Best Free Tools to Monitor, Manage, and Visualize Your Kafka Clusters in 2025.

Aiven for OpenSearch is a fully-managed service that provides an ideal way to run OpenSearch on Google Cloud. It is designed for companies looking to operate search applications without taking on the burden and complexity of self-managing the infrastructure in the cloud. Running on Google Cloud, the service is built upon core infrastructure like Google Compute Engine, Google Cloud Storage, and Private Service Connect.