GitFounders5 Open Source Alternatives to BigQuery
A list of 5 carefully selected open-source alternatives to BigQuery.
The open-source alternatives are ranked based on our custom ranking system and score. This system takes into account various factors to determine the best alternatives.
If you’re looking for alternative features or workflows, here is a prepared detailed list of BigQuery open-source alternatives — each with its own distinctive strengths and key features.
ClickHouse® is a real-time analytics database management system that delivers blazing fast query performance and efficient data processing. Trusted by leading companies, it empowers developers to build real-time data products with simplicity and reliability.
Key Features
- Blazing fast query performance for real-time analytics
- Developer-friendly with intuitive SQL interface
- Cost-effective with best-in-class compression ratios
- Scalable deployment options across cloud, on-prem, and local setups
- Seamless integration with a vast ecosystem of over 100 tools
- Proven performance at scale with support from major enterprises
ClickHouse offers a high-performance, column-oriented architecture optimized for real-time analytics. It supports a wide range of use cases such as observability, business intelligence, ML & GenAI, and fraud detection, while integrating seamlessly into your tech stack. Deploy on cloud, on-prem, or locally with transparent pricing options tailored for testing, production, and enterprise-scale environments.
Activeloop is an enterprise-grade database for AI that simplifies managing multi-modal data. It stores and queries images, videos, texts, vectors, and more, enabling developers to build high-performance machine learning applications with real-time data streaming and version control.
Key Features
- Stores multi-modal data including images, texts, videos, and vectors
- Real-time data streaming to ML frameworks
- Serverless tensor query engine with natural language support
- Dataset visualization and version control
- Integrates with LangChain, PyTorch, TensorFlow, and more
- SOC 2 Type 2 certified for data security
The tool provides a tensor-based database optimized for deep learning pipelines. Activeloop enables seamless data ingestion, querying, visualization, and version control for unstructured data. It integrates with frameworks like PyTorch, TensorFlow, and LangChain, and supports natural language queries and serverless tensor queries to improve retrieval accuracy.
Databend is an open-source, elastic, and cloud-native data warehouse designed for massive-scale analytics. It delivers lightning-fast data ingestion and query performance, making it a modern, cost-effective alternative to Snowflake.
Key Features
- Open-source and cloud-native data warehouse
- Elastic, workload-aware scaling for massive analytics
- SQL:2011 compliance with support for complex queries and time travel
- Native AI integration to enhance data analytics
- Robust security with RBAC, DAC, SOC 2, and GDPR compliance
- Seamless integration with popular data systems and visualization tools
- Multiple deployment options: Cloud, Enterprise, and Community
Databend empowers users to effortlessly manage and analyze large-scale data in the cloud with an open-source engine that is both elastic and workload-aware. The platform supports SQL:2011 compliance, time travel queries, and integrates natively with AI capabilities. Its seamless connectivity to data visualizations and lakes, alongside robust security features like RBAC and DAC, positions it as a versatile solution for diverse data needs.
Titan is an open source infrastructure-as-code tool designed specifically for Snowflake. It streamlines the provisioning, deployment, and security of various Snowflake resources using a declarative Python and YAML API.
Key Features
- Provision and deploy Snowflake resources
- Declarative Python and YAML Resource API
- Automated CI/CD and environment management
- Manage RBAC, users, roles, and data access
- Robust change management capabilities
Titan Core helps you provision, deploy, and secure Snowflake environments by enabling you to define resources such as users, roles, schemas, databases, integrations, pipes, stages, functions, and stored procedures. Using a declarative approach with Python or YAML, it automates CI/CD pipelines and manages RBAC and data access, serving as a powerful alternative to traditional tools like Terraform.
CrateDB is a distributed and scalable SQL database designed for storing and analyzing massive amounts of data in near real-time. It offers powerful hybrid search and real-time analytics capabilities with PostgreSQL compatibility and a Lucene-based search engine.
Key Features
- Distributed architecture with near real-time analytics
- PostgreSQL compatibility for seamless integration
- Hybrid search across various data types using Apache Lucene
- Automatic real-time ingestion and dynamic indexing
- Flexible deployment: cloud, on-premises, and edge
CrateDB empowers developers to execute ad-hoc queries on billions of records in milliseconds and perform complex aggregations across diverse data types. Its native SQL support, dynamic indexing, and flexible data schema accommodate structured, semi-structured, geospatial, and vector data. With multiple deployment options including cloud, on-premises, and edge, CrateDB is built for scalability and high performance.
Price comparison of BigQuery open-source alternatives
| Tool | Tier 1 | Tier 2 | Tier 3 | Details |
|---|---|---|---|---|
 | - Basic | - Scale | - Enterprise | Learn more |
 | $99 Pro | - Enterprise | - | Learn more |
 | $2 Databend Cloud - Small Instance | - | - | Learn more |
 | $0.069 Free Plan | $0.24 Dedicated Plan | - Custom Plan | Learn more |
* Pricing shown is based on publicly available information and may not reflect current rates. Visit each tool's website for detailed pricing information and additional tiers.
