Snowflake vs SingleStore

by Gralio Feb 28, 2025

Snowflake and SingleStore are powerful data platforms catering to different needs. Snowflake is best for robust data warehousing and analytics, while SingleStore shines in real-time applications requiring high-speed data processing. Choose Snowflake for complex data analysis and diverse integrations, and SingleStore for speed and real-time insights.

At Gralio.ai we help to simplify your decision-making process by offering detailed, side-by-side software comparisons like this one, to help you confidently choose the tool that aligns with your business goals.

This comparison was created by analysing 774 reviews and 60 websites, saving 4 hours, 48 minutes of reading.

Snowflake

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SingleStore

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About

Snowflake is a cloud-based data platform designed for businesses to store, manage, and analyze large amounts of data. It works like a giant, virtual warehouse for all your data, accessible from anywhere. Snowflake adapts to your needs, scaling its power and cost up or down on demand. This makes it suitable for tasks like analyzing customer trends, building data-driven applications, or sharing data securely with partners. Its strength lies in handling massive datasets with high speed and efficiency.

SingleStore is a database platform designed for speed and handling large amounts of data, making it suitable for applications requiring real-time analytics. It allows businesses to manage various data formats in one place, simplifying data infrastructure. SingleStore is used by companies of all sizes across various industries, notably in finance and technology.

Summary

Main difference

Snowflake excels in data warehousing and analytics for large datasets, integrating seamlessly with various data sources. SingleStore focuses on real-time analytics and transactional workloads, ideal for applications demanding high-speed data ingestion and processing.

Relative strengths of Snowflake (compared to SingleStore)

Strong data warehousing capabilities and diverse integrations for comprehensive data analysis.
Scalable architecture to handle massive datasets efficiently, adapting to evolving business needs.
Columnar storage for optimized analytical queries and performance.

Relative weaknesses of Snowflake (compared to SingleStore)

Limited machine learning capabilities compared to some competitors.
Can be more complex to set up and manage for real-time transactional workloads.
Potentially higher cost for smaller businesses with less demanding needs.

What companies are using Snowflake and SingleStore?

No data

Who should use Snowflake VS. SingleStore

Snowflake is a scalable cloud data platform ideal for data-driven businesses of all sizes. Users praise its scalability and ease of use, especially the query profile and seamless integrations. However, some find the new UI confusing and desire better unstructured data support. It's a robust solution for companies in various sectors, particularly those in technology, finance, and healthcare, seeking efficient data storage, management, and analytics for enhanced decision-making.

SingleStore is a real-time database platform ideal for businesses needing fast analytics on large datasets. It simplifies data infrastructure by managing various data formats in one place. Known for its speed and scalability, SingleStore excels in demanding industries like finance and technology.

Ideal for small businesses, medium businesses, and large enterprises.
Best fit for Software, IT & Telecommunications; suitable for various other industries including Healthcare, Finance, Retail, and more.

Ideal for small to large businesses needing real-time analytics.
Strong fit for finance and technology, applicable to various other industries.

Snowflake and SingleStore features

Supported

Partially supported

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Hybrid vector and full-text search

Supported

Snowflake supports hybrid search via Cortex Search, combining semantic and keyword matching.

Supported

SingleStore supports hybrid vector and full-text search using SQL.
Cloud database service for real-time workloads

Partially supported

Snowflake excels in real-time analytics but isn't designed for transactional processing.

Supported

SingleStoreDB is a cloud database service designed for real-time workloads, combining transactions and analytics.
Faster JSON analytics

Supported

Snowflake supports faster JSON analytics using its Variant data type, SQL extensions, and specialized functions.

Supported

SingleStoreDB supports faster JSON analytics for real-time insights.
Data Warehouse Integration

Supported

Snowflake excels in data warehouse integration, seamlessly connecting with diverse data sources like relational databases, cloud platforms, NoSQL databases, and streaming services. Its compatibility with third-party tools, data sharing capabilities, flexible architecture, support for semi-structured data, and query optimization prowess make it highly capable of integrating with other warehouse databases.

Supported

SingleStore integrates with other data warehouses using connectors, CDC, and data transfer tools.
SQL support

Supported

Snowflake fully supports querying data via SQL.

Supported

SingleStore supports SQL for querying data, including ANSI SQL.
Columnar storage

Supported

Snowflake stores data in a columnar format, meaning data for each column is stored together, separate from other columns. This is beneficial for data analytics and business intelligence applications where calculations are often performed over a single data column.

Supported

SingleStoreDB uses columnar storage by default, optimized for analytical queries.

Qualities

Value and Pricing Transparency

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Customer Service

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Ease of Use

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Reliability and Performance

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Ease of Implementation

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Scalability

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Snowflake and SingleStore Pricing

No data

See full Pricing page

No data

See full Pricing page

Snowflake and SingleStore review insights

Users love

The ability to easily scale warehouses based on requirements
Query profile is a very useful feature
The user interface is easy to implement and navigate
Seamless integration with various data tools

Excellent scalability and versatility for multi-model architectures.
Comprehensive and responsive customer support.
Combines row and column store benefits effectively.
Fast data processing and tooling.
High throughput for real-time aggregates and individual row retrieval.

Users dislike

Limited machine learning features
Data migration efforts are large to transfer everything from on premises to cloud
The new UI is too confusing
Unstructured data support is lacking

Difficult to debug issues and requires extensive back-and-forth with support.
Tedious tasks like updating enum columns.
Slow pipelines with limited logging.
Replication at the table level is lacking.
Lack of a reject file for pipeline loading errors.

Snowflake and SingleStore Ratings

Glassdoor

4.0/5

(749)

Glassdoor

4.0/5

(379)

Company health

Employee growth

20% increase in the last year

10% increase in the last year

Web traffic

1% increase in the last quarter

9% decrease in the last quarter

Financing

March 2022 - $2B

June 2022 - $464M

How do Snowflake's data sharing capabilities compare to SingleStore's for secure collaboration?

Snowflake's data sharing capabilities are generally considered more robust and mature than SingleStore's. Snowflake allows secure data sharing with other Snowflake accounts, as well as secure external sharing via Reader Accounts and secure data spaces. While SingleStore supports data pipelines and integrations, it doesn't offer the same breadth and depth of secure, direct data sharing features for collaboration that Snowflake provides. Snowflake's focus on data sharing as a core functionality makes it better suited for organizations with complex data sharing needs and a focus on secure collaboration with external partners.

Which platform, Snowflake or SingleStore, better supports real-time analytics for my specific data volume?

SingleStore is generally better suited for real-time analytics due to its focus on speed and handling of large datasets for real-time workloads. While Snowflake excels at large-scale data warehousing and analytics, its architecture is optimized for high throughput batch processing and complex queries rather than the immediate, low-latency responses needed for real-time applications. Therefore, if your data volume requires very rapid analysis and responses, SingleStore is likely the better choice.

What are the advantages of Snowflake?

Snowflake offers superior data warehousing integration capabilities, seamlessly connecting with various data sources. Its columnar storage, full SQL support, and SQL-based data transformation features enhance analytical processing. Furthermore, Snowflake's architecture allows for easy scalability, adapting to changing data demands.

What are the disadvantages of Snowflake?

Snowflake's disadvantages include limited machine learning capabilities compared to some competitors, potentially complex data migration processes for on-premise data, a user interface that some users find confusing, and less robust support for unstructured data. Additionally, its pricing model, while flexible, can become expensive as data storage and compute needs increase.

Alternatives to Snowflake and SingleStore

Microsoft SQL Server

Microsoft SQL Server is a database management system for businesses of all sizes. It helps you analyze various types of data and can be used in multiple environments, including on your servers and in the cloud. SQL Server offers high performance and strong security features. It allows developers to build applications using different programming languages and provides mobile business intelligence tools.

Databricks Data Intelligence Platform

Databricks Data Intelligence Platform is a cloud-based platform designed to help mid-size to large businesses manage and analyze data. It offers a range of tools for data warehousing, data engineering, data science, and machine learning, all in one place. Databricks aims to simplify data processes, reduce costs, and enable companies to build and deploy AI solutions. They are well-known for their work with open-source technologies, making them a popular choice for businesses invested in those ecosystems.

Google Cloud BigQuery

Google BigQuery is a fully managed data warehouse service that helps businesses analyze massive datasets to gain insights. It's serverless, so you don't need to manage any infrastructure, and it can handle data from various sources. BigQuery is designed for fast query processing, allowing you to quickly explore and analyze your data. It's a powerful tool for data-driven decision-making in any industry, regardless of company size.

Amazon Athena

Amazon Athena is a service that lets you analyze large datasets stored in Amazon S3 using standard SQL queries. It's serverless, so there's no infrastructure to manage, and you pay only for the queries you run. This makes it a cost-effective way to get insights from your data without the complexity of traditional data warehousing.

ClickHouse

ClickHouse is a database management system specifically designed for analyzing very large amounts of data quickly. It achieves its speed by storing data in columns rather than rows. This makes it especially good for generating reports from data like business transactions, website activity, or application performance logs. ClickHouse is open-source and can be used for free, or as a paid cloud service with additional features.

LeanXcale

LeanXcale is a database solution designed for speed and scalability. It handles both massive data sets and real-time information, making it suitable for various uses like operational reporting, analysis, and machine learning. LeanXcale aims to process transactions quickly and efficiently, particularly for financial services, through its unique technology. While supporting standard data management features, LeanXcale emphasizes its ability to handle large volumes of information quickly and efficiently.

Page co-authored by

Michal Kaczor

CEO at Gralio

Michal has worked at startups for many years and writes about topics relating to software selection and IT management. As a former consultant for Bain, a business advisory company, he also knows how to understand needs of any business and find solutions to its problems.

Tymon Terlikiewicz

CTO at Gralio

Tymon is a seasoned CTO who loves finding the perfect tools for any task. He recently headed up the tech department at Batmaid, a well-known Swiss company, where he managed about 60 software purchases, including CX, HR, Payroll, Marketing automation and various developer tools.

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