If you're looking for a replacement to Aiven, Cloudera is a good candidate. Its hybrid data platform securely ingests, processes and analyzes data in the cloud and on-premises, with a wide range of data services. The platform enables real-time insights, automated data pipelines, big data analytics and accelerated machine learning, and is suited for companies in financial services, manufacturing and healthcare.
Another good candidate is Qubinets. This SaaS platform streamlines the installation and operation of open-source data infrastructure so developers can focus on writing code. Qubinets provides managed open-source tools, a schema connector repository, native observability and customizable cloud environments. Its support for a variety of technologies, including event streaming and AI/ML tooling, and its pay-as-you-go pricing means it's a good fit for teams tackling complex data projects.
If you need a platform that centralizes and harmonizes data across an organization, Teradata could be a good choice. Teradata VantageCloud spans multiple workloads like AI/ML, lakehouses, data lakes and transactional workloads. It includes ClearScape Analytics for faster insights, trusted AI and pay-by-use pricing. The platform is designed to accelerate innovation, optimize resources and enable data-driven decision-making.
Last, if you want to build AI and analytics directly into your Postgres-based workloads, check out EDB Postgres AI. It provides a unified data layer, AI vector processing, an analytics lakehouse and hybrid data management. With high availability and performance, EDB Postgres AI supports transactional, analytical and AI workloads, making it a strategic technology asset for hybrid or multi-cloud environments.