Snowflakes vs. Firebolts: Compare Data Warehousing Platforms

ETL (Extract, Transform and Load) tools and software are powerful data management products designed to transfer and convert data to target repositories for analysis and use. TechRepublic’s ETL Top Product page covers the concept in-depth with business-use cases and product examples.

There is a diverse array of ETL tools on the market to cover a wide set of data manipulation needs. Two prominent ETA software products that can be considered among the best ETL tools are Firebolt and Snowflake.

What is a snowflake?

Snowflake features are listed in small boxes.
Photo credit: Snowflake

Snowflake is a cloud data platform available between AWS, Azure and Google Cloud providers. It works with data integration tools like Informatica, Talend, FiveTran, Matilion and others. In fact, it can be integrated with more than 140 data sources, data analytics and business intelligence platforms such as Alooma, Sisense, Datom and DBschema.

Snowflake relies on the concept of warehouses, which are clusters of node type computing resources that feature memory, storage, and CPU usage (note that you can’t actually tune node types, only overall warehouses. The amount of raw data in its native format.

According to the developers, if Snowflake is used as a data lake and data warehouse, there is no need for ETL process “since no pre-conversion or pre-scheme is required.”

Scalability is a strong factor with Snowflake and it offers auto-scaling options for adjusting cluster operations to suit resource processing needs. It can automatically suspend inactive clusters to optimize performance and cost, looking at how resource usage is a driving factor with data management.

Work processing, where data is actually manipulated and worked, is a standard unit of measurement that is defined in hours per day.

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The main feature of snowflakes

Snowflake Documentation lists the top key features as follows:

  • Security, governance and data protection: This function controls data access through robust authentication processes, TLS security, granular access policy, data isolation, and disaster recovery.
  • Standard and extended SQL support: SQL support on Snowflake is strong, complying with the 1999 SQL standard.
  • Tools and interfaces: Snowflake offers a web-based GUI and a SnowSQL Python-based CLI. Warehouses can be managed from any one of the above interfaces.
  • Connection: Connectivity is an integral part of data access and management, facilitating the use of the Snowflake connector, which works with Python, Spark, Node.js, Go Snowflake, .NET, JDBC, ODBC and PHP PDO.
  • Data Import and Export: Snowflake has made possible a wide range of data import / export processes; Supported character encoding, compressed files, local or cloud storage files and data using CSV, TSV, JSON, Avro, ORC, Parquet and XML formats.
  • Information sharing: This function shares information with other Snowflake accounts or vice versa.
  • Database Copy and Failure: Snowflake protects databases with this option for copying and syncing databases between Snowflake accounts in the same or different regions.

Snowflake Dashboard lets you monitor user activity per warehouse, per database, and over time:

Snowflake dashboard featuring blue and gray graphs.
Image Credit: Table

Starter templates let you easily monitor performance-like elements out of the box.

Snowflake performance menu with multicolor bar graphs.
Image Credit: Sigma Computing

Price: Snowflake offers a free trial with the use of $ 400 Their pricing model is complex due to the numerous functions involved in storing and processing data across different organizational sizes and requirements. It is ideal for ETL software and ETL tools for big data. However, in short, the cost is based on the storage and resources used.

The pricing guide covers these details and includes two support price examples where a small company will spend T 22,878 per year on a 10 hour daily time slot, storing 5TB of compressed data with eight users having similar needs. A large company with different needs of 17 users will save T 118,807.20 per year working on an 11 hour daily time slot with 65TB of compressed data stored.

Snowflake also provides a simple computer cost interface that helps you evaluate warehousing and cost over time.

Multi-colored bar graphs at the expense of snowflakes.
Photo credit: Snowflake

What is a firebolt?

The features of Firebolt are graphically arranged.
Photo Credit: Firebolt

SQL Editor at Firebolt.
Image Credit: GetApp

Firebolt is a competitor to Snowflake’s AWS Cloud Data Warehousing products that integrate with the Looker, Mockplay and Sciences Business Intelligence platforms. Its developers promote product speed and performance to achieve sub-second analytics processing. According to database architect Robert Meyer, “Firebolt is 182x faster than any other option. A customer gets 3 times faster performance and 10 times less cost or 30 times price-performance advantage than their Snowflake installation.

Meyer aggressively cites Firebolt’s advantages over higher data manipulations, such as “ad hoc analysis, larger complex questions against larger data sets, semi-structured data questions, and streaming analysis or continuous ingestion.”

Firebolt allows you to tune individual node types to specify the desired storage and resource limits.

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The main feature of the firebolt

Firebolt Documentation lists these product features that are generally self-explanatory and similar to Snowflake in form and function:

  • Access control / permission
  • Ad hoc questions
  • Data capture and transfer
  • Manage data dictionary
  • Data extraction
  • Information on the combination of different ingredients
  • Data transfer
  • Copy data
  • Data storage management
  • Data conversion
  • Database conversion
  • Database support
  • ETL – Extract / Transfer / Load
  • Mobile access
  • Multiple programming languages ​​supported
  • Performance analysis
  • Relative
  • Reporting / Analysis
  • Third party integration
  • Workflow management

The Firebolt Dashboard lets you monitor important things like connectors, services, computing, external data and storage.

Firebolt dashboard with red icons and fonts.
Photo Credit: Firebolt

Price: A free trial of Firebolt is available and its paid price model is like Snowflake that it is complex and based on the cost of resources. The Firebolt pricing page also contains thematic examples, noting that a customer pays $ 3,616 per hour for 2.36 data usage across 64 virtual CPUs and 256GB of RAM. Compute costs start at less than 1 / hour, and the base storage cost for “as much data as you need” is $ 3 / hour with an average data cost of ~ 23TB.

How to decide between two data warehousing platforms

Snowflakes are seen as a basic product for more general needs where performance is less important than achieving data results. It seems to be suitable for small shops with a standard array of requirements. To recap, it has a wide range of availability in terms of running on AWS, Azure and Google Cloud. It can integrate with many more data sources and BI platforms than Firebolt.

The strength of firebolts lies in performance and flexibility. Independent reviews, such as, confirm that Firebolt’s speed is higher than other providers, including Snowflake. Snowflake does not use indexing, where Firebolt does it with a higher octane mixture of query performance. Firebolt allows you to tune individual node types, whereas Snowflake restricts you to tuning warehouses only.

Firebolt was created for AWS, so it’s important to contrast it with Snowflake, which is available for AWS, Azure and Google Cloud.

Larger stores or businesses with a more diverse demand that rely on rigorous, detailed data messaging and quick analytical results will probably pay better rent with Firebolt, which seems to have a more tolerable price structure.

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