Trino & Presto Alternative

Presto and Trino are general purpose data processing engines. These distributed systems are used to query data that resides externally in a data lake or other systems. Presto originated from the Hadoop ecosystem and Trino in turn evolved from PrestoSQL. These should be viewed as complex Federated Query Engines with limited performance optimizations when it comes to delivering fast, responsive interactive analytics applications. As a result of complexity and higher TCO these technologies may not be a fit for everyone.

Firebolt was designed for low-latency analytics and dashboards from the ground up. Firebolt is a Cloud Data Warehouse with compute and storage optimizations geared towards big data, fast data challenges. Building, scaling and delivering data products is more than querying external data sources. Data products require consistent performance against unified data without processing redundancies. That's what Firebolt delivers! Additionally, Firebolt makes it easy to onboard data and run analytics without a complex architecture.

Architecture 

Presto / Trino

Presto and Trino are Federated Query Engines that are implemented in the form of clusters. These are primarily used for ad-hoc query use cases and large scale data transformations. Both engines query data-in-place in a data lake or other data sources through data connectors. Presto and Trino come with a high degree of complexity due to the distributed architecture and federation capabilities. Additionally, external storage optimizations are required.

Firebolt logo

Firebolt is a columnar Data Warehouse architected from the ground up for low-latency analytics workloads at TB++ scale with built-in storage optimization. No external tools or optimizations needed. Firebolt is a Cloud Data Warehouse designed with zero cluster management and simplicity in mind.

Decoupled Compute and Storage 

Presto / Trino

Presto and Trino clusters provide the compute required to perform CRUD operations against external storage.  There are no options to control or optimize storage. Detailed understanding and tuning of performance is required both on Presto/Trino end as well as the corresponding data sources and respective connectors. Cluster behavior and functionality vary by connectors. For data lake applications, proper partitioning is a must for effective data access. 

Firebolt logo

Decoupled compute and storage is a key design element in Firebolt, allowing independent scaling of compute and storage. Provides control and visibility of resources for easy, cost effective scaling. No additional performance management is needed, as storage is optimized automatically. Firebolt is not focused on federated queries, connector behavior is not applicable. Furthermore, multi-level data pruning in the form of partition, tablet and data range is automatic and does not require additional management.

Performance

Presto / Trino

Scales well for ad hoc queries and data transformations. Not designed for sub-second latency applications. Presto/Trino customers typically leverage additional stand-alone accelerator technologies like Druid or Pinot to address these requirements. This results in complexity and costs. 

Firebolt logo

Firebolt offers sub-second latency by leveraging optimized file format along with specialized indexes. Firebolt engines address high concurrency use cases.

Indexes

Presto / Trino

Presto/Trino support data pruning through partitions, however, they do not offer specialized indexes to address fine grained pruning for fast access. Some managed offerings of Trino offer limited indexing capabilities with limited applicability.

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Firebolt’s  zero maintenance indexes are storage efficient and provide rapid data access without the management overhead.

The Firebolt Advantage 

Cloud-native architecture

SaaS with operational simplicity
Native decoupling of storage & compute
Easy Workload Isolation & Elastic Scaling

Performance

Sub-second Latency for Big Data
High Concurrency Queries 
Aggregating indexes with automatic query rewrite

Cost Efficiency

Highly efficient and granular Compute 
Save costs with Auto Stop
Lower TCO with scalable object storage

Integration with Modern Data Stack

SQL Simplicity with ANSI-SQL compliance
REST APIs / SDKs 
Ecosystem Integrations

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