Partitioning a distributed system into segments allows systems to prioritize the elements of CAP that are most important for certain data or operations. Some architectures incorporate multiple separate databases for different use cases. For example, the online marketplace Etsy uses a MySQL database for strong consistency; high-availability Redis for in-memory caching; and Apache Kafka, which prioritizes partition tolerance, for streaming data.
Many new databases attempt to overcome the limitations described by the CAP theorem. SQL database that uses a Raft consensus algorithm to ensure that all replicas of the database agree on qatar whatsapp number data the order of writes so that the database remains available even if some replicas fail. This allows CockroachDB to offer strong consistency and availability, even in the face of network partitions. TiDB, another newer distributed SQL database, utilizes a Raft consensus algorithm to provide strong consistency and availability for large-scale applications.
The Future of Database Design
New technologies and trends have the potential to further address the tradeoffs of the CAP theorem. Many database designers are shifting to cloud-based architectures, which have a number of advantages over on-premise databases, including scalability, elasticity, and fault tolerance. Multi-cloud deployments are capable of making hybrid database architectures easier to implement.