Will HTAP database eat both OLAP & OLTP? Chat with Moritz & Christian at CedarDB
Jul 22, 2024
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CedarDB's founders dive into their innovative all-in-one database, blending OLAP and OLTP for greater efficiency. They discuss how their architecture boosts performance by adapting to modern hardware. The podcast explores the challenges of Hybrid Transactional/Analytical Processing (HTAP) systems and the need for tailored solutions. They also touch on enhancing PostgreSQL compatibility while forecasting the evolving landscape of SQL and data management. CedarDB aims to revolutionize data infrastructure for mid-sized enterprises.
CedarDB combines OLAP and OLTP capabilities into a single platform, enabling users to efficiently manage diverse workloads with enhanced performance.
The advanced query optimizer of CedarDB transforms complex SQL queries into highly efficient machine code, maximizing CPU utilization for accelerated data processing.
Deep dives
Introduction to CedarDB and its Capabilities
CedarDB is an innovative all-in-one database system designed for modern hardware and data processing needs. Positioning itself as a next-generation alternative to traditional databases like Postgres, it combines SQL-based relational capabilities with enhanced performance and efficiency. By allowing users to leverage their existing SQL knowledge, CedarDB simplifies data analysis and eliminates the need for numerous tools and complex languages. This streamlined approach is reflected in its architecture, which aims to provide faster data access and analysis, similar to the convenience once enjoyed in the 90s with Postgres.
Performance Optimization Through Advanced Query Processing
A key differentiator of CedarDB is its advanced query optimizer, which is built from the ground up for contemporary hardware. This optimizer can generate efficient query plans even for complex queries involving multiple joins, allowing users to write standard SQL without worrying about how the database will execute it. CedarDB compiles these optimized plans directly into machine code, achieving performance levels akin to hand-written C code, thus maximizing the capabilities of the underlying CPU. The system also allows for high memory processing speeds, efficiently utilizing the available memory to ensure swift query execution.
The Evolution of Database Systems and HTAP Integration
The podcast emphasizes the growing necessity for hybrid transactional and analytical processing (HTAP) systems like CedarDB, which seamlessly integrate both analytics and transactional workloads. It acknowledges that while Postgres has historically performed both functions, it has not been perceived as an HTAP system, with many users opting for specialized systems due to perceived limitations. CedarDB aims to fill this gap by providing a single platform that can handle diverse workload requirements efficiently. The discussion highlights that the transition from traditional single-purpose systems to HTAP solutions has been slow due to engineering challenges and the time required to develop comprehensive systems like CedarDB.
Transitioning to CedarDB and Data Management Strategy
CedarDB offers flexibility in transitioning from existing database systems, allowing users to integrate it gradually rather than requiring an immediate overhaul. This integration helps to eliminate the complexities of maintaining multiple systems and synchronizing data, which can lead to inconsistencies and delays in processing. By positioning itself as a singular source of truth, CedarDB enhances data consistency and streamlines operations by merging transactional and analytical processes. The system supports distributed storage, allowing for data to be stored in cost-effective object storage, ensuring that users can manage large datasets efficiently without compromising performance.
Ian and Tim sat down with the cofounders of CedarDB (https://cedardb.com/) that's building a all-in-one database that merges both OLAP and OLTP into one. Listen to our chat to hear how they got started from the academics and now jumping into making this database to take on all workloads.
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