Powerful Firestore management with SQL
Jetspike is a data analytics platform for Firestore that enables you to run complex SQL queries, optimize performance and generates source code
Dive deep into data
Compose, optimize and run complex SQL queries. Our advanced visualization and analytics tools help you to turn your data into insightful reports
Real-time SQL to code
Generate node.js code from your SQL automatically, including built-in functions, joins and grouping
Run by one click
Design and run your queries from an interactive web interface without the need to build and host any client application
Focus on performance
Analyze execution time and number of backend calls in individual parts of the query to achieve optimal performance
Overcome the limitations of NoSQL databases while keeping their benefits
NoSQL databases have excellent performance and scalability, but this comes at the costs of limited features. Many functions of traditional SQL datbases are missing.
Jetspike gives you additional capabilities on top of Firestore for fast and efficient data analytics without the need to build, compile and host a client application to access your cloud-stored data.
Advanced SQL functionality for your Firestore
With an industry standard query language your team is already familiar with
- Subqueries
- SELECT, INSERT, UPDATE, DELETE
- JOIN, GROUP, UNION
- Built-in Functions
- Stored Views
Find the optimal plan for you
unlimited by time
- 20 queries / day
- 5 seconds execution time
- 256 MB RAM
- Up to 100 rows returned
- Up to 20 rows modified
- Basic SQL
$189 if billed yearly
- 250 queries / day
- 10 seconds execution time
- 512 MB RAM
- Unlimited rows returned
- Unlimited rows modified
- Advanced SQL
- Stored views
$399 if billed yearly
- 1000 queries / day
- 15 seconds execution time
- 1024 MB RAM
- Unlimited rows returned
- Unlimited rows modified
- Advanced SQL
- Stored views
Advanced Use Cases
Best way to learn a technology is to use it. In our advanced example, we build a complex report joining records from multiple collections and performing data aggregation. We will show how to solve challenging problems in a way you can encounter in your own applications.
