Compare IBM Db2 Big SQL vs. PuppyGraph in 2025

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Description

IBM Db2 Big SQL is a sophisticated hybrid SQL-on-Hadoop engine that facilitates secure and advanced data querying across a range of enterprise big data sources, such as Hadoop, object storage, and data warehouses. This enterprise-grade engine adheres to ANSI standards and provides massively parallel processing (MPP) capabilities, enhancing the efficiency of data queries. With Db2 Big SQL, users can execute a single database connection or query that spans diverse sources, including Hadoop HDFS, WebHDFS, relational databases, NoSQL databases, and object storage solutions. It offers numerous advantages, including low latency, high performance, robust data security, compatibility with SQL standards, and powerful federation features, enabling both ad hoc and complex queries. Currently, Db2 Big SQL is offered in two distinct variations: one that integrates seamlessly with Cloudera Data Platform and another as a cloud-native service on the IBM Cloud Pak® for Data platform. This versatility allows organizations to access and analyze data effectively, performing queries on both batch and real-time data across various sources, thus streamlining their data operations and decision-making processes. In essence, Db2 Big SQL provides a comprehensive solution for managing and querying extensive datasets in an increasingly complex data landscape.

Description

PuppyGraph allows you to effortlessly query one or multiple data sources through a cohesive graph model. Traditional graph databases can be costly, require extensive setup time, and necessitate a specialized team to maintain. They often take hours to execute multi-hop queries and encounter difficulties when managing datasets larger than 100GB. Having a separate graph database can complicate your overall architecture due to fragile ETL processes, ultimately leading to increased total cost of ownership (TCO). With PuppyGraph, you can connect to any data source, regardless of its location, enabling cross-cloud and cross-region graph analytics without the need for intricate ETLs or data duplication. By directly linking to your data warehouses and lakes, PuppyGraph allows you to query your data as a graph without the burden of constructing and maintaining lengthy ETL pipelines typical of conventional graph database configurations. There's no longer a need to deal with delays in data access or unreliable ETL operations. Additionally, PuppyGraph resolves scalability challenges associated with graphs by decoupling computation from storage, allowing for more efficient data handling. This innovative approach not only enhances performance but also simplifies your data management strategy.