Comparisons

VeloDB vs Snowflake

  VeloDB is designed for real-time data analytics with strong scalability. Snowflake is a cloud-based data warehouse and analytics platform. When it comes to real-time analytics, VeloDB shows higher concurrency, faster queries at a fraction of the cost.

Why Choose VeloDB

secondsminutes

Real-Time Data Latency

4-5x

Faster Queries

10x

Higher Concurrency

3-5x

Cost Efficiency

By making the switch to VeloDB for our real-time analytics platform, we've seen query speeds boost 3-10x faster and costs dropped nearly 50% compared to Snowflake. Plus, VeloDB's strong support for diverse analytical workloads—like complex searches, multi-table joins, and a variety of aggregations—makes it ideal for analytics that need to be both swift and adaptable.

Global Leading SaaS Vender

VeloDB

  • Deployment

    Supports three deployment options:

    Cloud-native SaaS service on AWS, Azure, and GCP
    Cloud-native BYOC service on AWS, Azure, and GCP
    On-premise deployment with enterprise-grade reliability
  • Real-Time Updates
    High-throughput real-time data updates reach millions of records per second
    Consume data from sources like Flink, Kafka, and APIs in real-time, with data visibility in seconds
  • Data API
    Supports Arrow Flight for high-speed data reading
  • Rich Indexes
    Skip Index: Minmax Index, BloomFilter Index
    Point Query Index: Prefix Index, Inverted Index
  • Materialized View
    Supports synchronous materialize view, real-time data refreshing
    Supports asynchronous materialized view for multi-table
  • Use Cases
    Real-Time Analytics
    Data Warehouse and Lakehouse
    Logging and Observability

Snowflake

  • Deployment
    Supports only Cloud SaaS
  • Real-Time Updates
    Not ideal for frequent data updates
    Batch data ingestion
  • Data API
    Only supports low-speed data reading via JDBC, ODBC
  • Rich Indexes
    Only supports skip index (Minmax Index, BloomFilter Index)
  • Materialized View
    No support real-time data refreshing
    No support for asynchronous materialized view
  • Use Cases
    Supports data warehouse and lakehouse, yet not ideal for real-time analytics

Performance Comparison

TPC-H SF100 Benchmark

The TPC-H benchmark with a scale factor of 100 (SF100) is a widely used standard for evaluating database performance. It includes a set of complex SQL queries designed to simulate real-world business intelligence workloads.

For comparison of query performance, models with similar costs were selected:

  • Snowflake Standard (Gen2),Large, Enterprise
  • VeloDB Cloud with 192C configuration
TPC-H SF100 Benchmark

TPC-DS SF1000 Benchmark

The TPC-DS SF1000 Benchmark evaluates data warehouse performance using a 1TB dataset with 6.35 billion records across 24 tables.

It includes 99 complex queries to test joins, aggregations, and subqueries. Based on a snowflake schema, it simulates real-world sales scenarios. The 1TB scale is challenging due to query complexity.

TPC-DS SF1000 Benchmark

ClickBench

ClickBench is a benchmarking tool to evaluate the performance of analytical databases. It focuses on testing the performance of large, flat tables rather than complex multi-table joins. It uses real-world data from a major web analytics platform, covering typical scenarios such as clickstream analysis and structured logs.

For comparison of query performance, models with similar costs were selected:

  • Snowflake Standard (Gen2),Large, Enterprise
  • VeloDB Cloud with 192C configuration
ClickBench