Firebolt vs PostgreSQL
for Fast Analytics and Reporting

Customers adopt PostgreSQL as it is easy to start for most Online Transaction Processing (OLTP) applications. To deliver fast analytics, PostgreSQL customers need to take on the complexity of parallel query tuning, partition management, materialized views and continuous optimization. Firebolt is a scalable alternative to running your PostgreSQL based analytics workloads without the complexity. Firebolt provides highly efficient data pruning through sparse indexes and simplified partition management to deliver warp speed dashboards and thus offloading your production PostgreSQL instance. Additionally, PostgreSQL databases require expensive block storage. Firebolt leverages object storage that costs significantly less and has unlimited scalability.

Built for

Firebolt vs PostgreSQL

Architecture

Postgres is a row-based RDBMS architected with OLTP workloads in mind. A full table scan would be required to examine even a subset of columns, in the absence of right indexes. As your database grows, the performance problems get worse.   

Firebolt logo

Firebolt is a columnar Data Warehouse architected from the ground up for low-latency analytics workloads at TB++ scale. Easy to scale and isolate workloads, thanks to the decoupled compute and storage architecture.

Storage

PostgreSQL leverages expensive, block storage for primary data storage.  This has scalability, cost and performance limitations. Block storage costs over 4X the cost of object storage and customers have to manage performance limitations in terms of IOPS and throughput.

Firebolt logo

Datasets are compressed and stored on tiered object storage for high performance and capacity with a lower TCO. Object storage combined with Firebolt’s compressed F3 file format reduces cost, eliminates storage management and is optimized for performance.

Partitioning and Parallel Query for Big Data

Partition management and parallel query tuning help ingest and query large volumes of data. However, these introduce complexity in management.

Firebolt logo

Firebolt uses sparse indexes for highly efficient data pruning. Partitions are flexible and optional. No shard management needed for scale-out. Also, Firebolt query optimization and vectorized processing eliminate the heavy lift of parallel query tuning.

Materialized Views 

PostgreSQL Materialized views require manual refresh, take significant time to refresh and do not have query rewrite capabilities.

Firebolt logo

Firebolt’s aggregating indexes are defined once, incrementally auto-synced at ingest and data can be queried at index speed immediately. No query rewrites needed.

Indexes

In the PostgreSQL world, indexes are rarely used for analytics workloads, as they introduce significant ingest, storage and maintenance overhead.

Firebolt logo

Firebolt’s zero maintenance indexes are storage efficient and provide blazing speed without the management overhead.

Read Replicas

Offloading analytics and reporting through read replicas introduces cost and management complexity.  

Firebolt logo

Firebolt’s hardware efficiency and 1-click scale up/down capabilities allow you to easily support high concurrency workloads. No read replicas needed.

Pricing

Managing scale-out clusters in PostgreSQL is complex  with high infrastructure and management costs. Additionally, reliance on block storage requires constant management of capacity vs IOPs or Throughput as required by the workload. These challenges can result in significantly higher costs for customers embarking on running analytics workloads on PostgreSQL.

Firebolt logo

Firebolt eliminates cluster management complexities by providing a SaaS model that can be scaled out easily. Additionally workload separation or isolation is possible with the same-shared data. No need to copy data for reporting or different workloads. Firebolt’s F3 file format on object storage and compute efficiency reduce data storage and processing costs for analytics workloads.

Firebolt Performance Advantage 

Results below illustrate Firebolt performance gains with smaller and cheaper clusters Vs PostgreSQL customer.

The Firebolt Advantage 

SaaS

No infrastructure or software to manage
No more vacuum and analyze
Easy to adopt with native Postgres dialect

Performance

Elastic scaling, decoupled storage & compute
Columnar Storage with Specialized Indexes
High concurrency without read replicas

Transparent pricing

Granular control over instance types
Save costs with Auto Stop
Lower TCO with object storage

Get started with Firebolt

Some happy clients:

Firebolt immediately gave us faster performance at a much greater scale, which let our customers analyze huge datasets with sub-second performance. It also gave us the flexibility to deliver complex data features at a much faster pace

Yoav Shmaria
VP R&D, Platform.
SimilarWeb

Firebolt has outperformed all other data serving SQL engines we have tested. It is built by engineers - for engineers

Roy Miara
Engineering Manager
Explorium

With Firebolt, our 1000 Looker users can now run any analytics against billions of rows and terabytes of data, in seconds or less.

Alexandra Sudilovski
S. BI Expert & Looker Guild M.
AppsFlyer
AWS Technology Partner
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