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Gluent Query Engine - FAQs
Frequently Asked Questions About Gluent Query Engine
Gluent Query Engine is designed to push down as much processing and filtering to the target platform as possible when retrieving virtualized data to satisfy existing RDBMS SQL queries. This includes pushing down one or more of the following for processing on the target platform:
- Predicates (i.e., the filters in the WHERE clause)
- Projections (i.e., to retrieve only the columns required by the query)
- Aggregations (using our Advanced Aggregation Pushdown feature)
- Join filters (using our Join Filter Pulldown feature)
- Joins (using our Join Pushdown feature)
- Data type conversion and formatting (for optimal performance).
Gluent Data Platform creates a hybrid architecture that allows data stored in both your RDBMS and your target platform to be accessed seamlessly. Data from a table can be spread across the RDBMS and your target platform. When a query executes, parts of the query execute on the RDBMS while other parts execute on the target platform. The goal is to push as much processing down to the target platform as possible, while returning only the minimum amount of data needed to the RDBMS. Joins can be pushed down entirely if the required tables are present in the target platform. This is particularly useful when doing joins with multiple large fact tables. Gluent Query Engine has several techniques and features to push down filtering and join logic to the target platform to avoid moving large datasets and keeping hybrid joins performant.
Yes, standard ANSI SQL is fully supported. Gluent Data Platform supports all standard SQL supported by Oracle Database including extensions such as PL/SQL.
Gluent Data Platform keeps the original SQL engine in play, eliminating the need to rewrite any application code and allowing transparent access to the data offloaded to your target platform. Existing PL/SQL continues to work in Oracle database deployments. Applications continue to connect to Oracle (usually with a much smaller footprint), which processes the incoming SQL and proprietary extensions such as PL/SQL. The heavy lifting is pushed down to the target platform by Gluent Query Engine. Having more data consolidated to the target platform maximizes the amount of processing that can be pushed down.
Gluent Data Platform uses open-source SQL engines on Hadoop and is certified with Hive (with or without LLAP), Impala and Spark. When accessing other platforms such as Google BigQuery, Gluent Data Platform utilizes that platform’s recommended SQL interface.
Yes, you can access your “big data” directly from your RDBMS. Gluent Query Engine allows you to access data that is native to your modern data platform directly and in real-time from your RDBMS without persisting the data in the RDBMS. This feature is enabled by a Gluent Offload Engine component called Present.
Tables that can be queried via Google BigQuery or Hive/Impala (e.g., Parquet, Avro, CSV, JSON) can be presented to your RDBMS, where they can be queried using the existing RDBMS SQL syntax and interface.
This functionality makes it very easy to share data from new modern data platforms back to your existing relational database systems.
Yes, Gluent Data Platform supports queries which run from the RDBMS in parallel.