How Aiven Keeps Open-Source Data Infrastructure on Any Cloud

Open-source databases and streaming systems are easy to adopt. Operating them reliably in production is a different job.

Running Apache Kafka means handling tasks like provisioning, patching, managing brokers, setting up failover, ensuring security, planning storage, and monitoring. PostgreSQL also requires work such as backups, replication, upgrades, extensions, and recovery. ClickHouse is great for high-volume analytics, but teams still have to manage the underlying infrastructure.

Aiven’s approach lets teams use familiar open-source technologies while handing off much of the operational work. The platform offers managed services like Kafka, PostgreSQL, ClickHouse, OpenSearch, MySQL, Valkey, Grafana, and more, across multiple cloud providers. Teams pick the service and where it runs, and Aiven takes care of most infrastructure management.

This is helpful for engineering teams who want to use open-source tools but don’t want to spend most of their time on database and streaming operations.

Open source still creates an operations workload

Open source lets teams use popular technologies without locking them into proprietary databases or messaging systems. However, it doesn’t eliminate the work needed to keep these systems running.

If you host Kafka yourself, you still need to provision, patch, monitor, and recover brokers when nodes fail. You also have to plan for capacity as throughput grows, and storage costs rise as you keep data longer.

PostgreSQL requires ongoing maintenance, backups, planning for replication, recovery steps, and managing versions. With ClickHouse, there’s even more to do when your analytical datasets get big enough to need distributed computing and storage.

Aiven acts as a bridge between open-source software and the cloud infrastructure underneath. The company says its managed services handle provisioning, patching, scaling, backups, security, and recovery from failures. They also offer a 99.99% uptime SLA for production services.

Customers still use Kafka, PostgreSQL, or ClickHouse, but Aiven takes on much of the responsibility for running these services.

One platform across several cloud providers

Aiven lets you deploy on AWS, Google Cloud, Microsoft Azure, DigitalOcean, and other providers. You can also use their Bring Your Own Cloud model, where Aiven runs the service inside your own cloud account.

This means you don’t have to pick a database based on a single cloud provider. Instead, you choose the open-source service you want and then decide where to run it.

Aiven gives you one API and console to manage all its services. This is helpful if your data stack uses several technologies. For example, your team might use Kafka for event streams, PostgreSQL for transactions, and ClickHouse for analytics, all without having to manage each service in a different way.

Taking Kafka operations off the engineering team

Kafka shows why managed open source is appealing. It’s popular for event streaming, but running production clusters takes ongoing work.

Aiven for Apache Kafka handles provisioning, patching, backups, security, and failover. It also offers automatic node recovery and supports multi-node clusters across different availability zones.

Storage is another challenge. Aiven supports tiered storage, so older data can move to object storage while compute and storage scale separately. This means you don’t have to add more broker disk space just because you need to keep data longer.

The service also comes with a Karapace-based Schema Registry, predictive consumer lag monitoring, and over 50 connectors to move data between Kafka and other systems.

Teams using Kafka don’t have to handle every infrastructure task needed to keep the cluster running.

PostgreSQL without the routine database administration

PostgreSQL is easier to start with than many distributed data systems, but running it in production still takes regular administrative work.

Aiven for PostgreSQL takes care of database administration for deployment and availability. It supports features like write-ahead logging, point-in-time recovery, replication, and active standbys. The platform also works with over 50 PostgreSQL extensions, such as pgvector, PostGIS, TimescaleDB, pg_cron, and pgaudit.

Aiven also offers a query optimization tool that looks at things like query structure, table setup, and indexing.

Aiven’s La Redoute case study shows the operational benefits. The retailer said its database team used to spend up to 90% of their day on maintenance, patching, and upgrades. After switching to Aiven, they had more time for business projects.

This is the main reason to use managed PostgreSQL: you keep the familiar technology, but routine administration takes up less engineering time.

ClickHouse fits into the same managed stack

ClickHouse brings a different kind of workload. It’s built for online analytical processing and is often used when teams need to quickly query large datasets.

Aiven manages the infrastructure for ClickHouse and lets you scale compute and storage separately. Its tiered storage feature moves older, less-used data to object storage.

Aiven also offers managed connections between Kafka and ClickHouse, so streaming events can be written directly into ClickHouse tables. You can also analyze PostgreSQL data in ClickHouse using connectors or federated queries.

This setup creates a clear division of work in your data stack: Kafka manages event streams, PostgreSQL stores transactional data, and ClickHouse handles analytics.

These technologies stay as separate open-source systems, but you can manage their infrastructure and connections all in one place.

Keeping cloud choice while reducing infrastructure work

Managed services are a trade-off. Teams give up some control over infrastructure to a provider, but they get less operational work in return. The key question is how much control you keep.

Aiven’s approach separates your data technology from the cloud provider. You can run the same managed open-source services across supported clouds, or use BYOC if you need to keep data in your own account for reasons like data residency, network setup, existing contracts, or internal policies.

This doesn’t take away all responsibilities from the engineering team. You still need good data models, capacity planning, access controls, query design, and monitoring. The main change is that Aiven handles the infrastructure for Kafka, PostgreSQL, ClickHouse, and other managed services.

For teams already committed to open-source data tools, that distinction can be useful. They can keep the technologies their developers know while reducing the time spent patching databases, recovering nodes, managing brokers, and maintaining the infrastructure around them.