Database & Data Management · head to head
Apache Druid vs BigQuery
Apache Druid
Database & Data Management
Real-time analytics database for sub-second OLAP queries
- From
- Free
- Rated
- -
BigQuery
Database & Data Management
Serverless, highly scalable enterprise data warehouse
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Apache Druid open-source offering lacks high-availability, distributed architecture, and enterprise security features; BigQuery query costs can become substantial for organizations with high query volumes
- They diverge on capability: Apache Druid covers Real-time Ingestion, BigQuery covers Serverless Architecture.
Where they differ
Only the attributes on which Apache Druid and BigQuery actually diverge.
| Attribute | Apache Druid | BigQuery |
|---|---|---|
| Pricing model | open-source | usage-based |
| Platforms | Docker, Kubernetes, Native deployment (Java-based) | Web, Cloud API |
| Founded | 1999 | 2008 |
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Database & Data Management).
What each one covers
Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.
Only in Apache Druid
- Real-time Ingestion
- Sub-second Queries
- Column-oriented Storage
- Streaming Integration
- Approximate Algorithms
- Flexible Schemas
- Time-based Partitioning
- Kafka
Only in BigQuery
- Serverless Architecture
- Petabyte Scale
- Real-time Analytics
- Machine Learning
- Geospatial Analysis
- Streaming Ingestion
- Standard SQL
- Looker
What people use each for
The jobs each tool is most often brought in to do.
Apache Druid
- Real-time analytics platforms ingesting millions of events per second from streaming sourcesnot BigQuery
- Applications requiring sub-second queries over high-cardinality datasets (billions to trillions of rows)not BigQuery
- Time-series and event analysis at massive scale with columnar storage efficiencynot BigQuery
BigQuery
- Business intelligencenot Apache Druid
- Data warehousingnot Apache Druid
- Real-time analyticsnot Apache Druid
- Reportingnot Apache Druid
- Machine learningnot Apache Druid
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Apache Druid
- Open-source offering lacks high-availability, distributed architecture, and enterprise security features
- Requires native integration with Apache Kafka or Amazon Kinesis for real-time ingestion; custom integrations need development
- High-concurrency query support (hundreds of thousands QPS) requires significant cluster infrastructure investment
BigQuery
- Query costs can become substantial for organizations with high query volumes
- Data egress from Google Cloud incurs additional charges
Pricing, plan by plan
Apache Druid
FreeNo published plan breakdown. See the Apache Druid review.
BigQuery
Free- Free TierFree
- 1TB queries/month
- 10GB storage/month
- Standard support
- On-demand$6.25/TB
- Pay per query
- Pay per storage
- All features
Which should you pick?
Choose Apache Druid if
- You need real-time ingestion.
- You want to start without paying.
- You work on Docker, Kubernetes, Native deployment (Java-based).
- You also want sub-second queries.
Choose BigQuery if
- You need serverless architecture.
- You want to start without paying.
- You work on Web, Cloud API.
- You also want petabyte scale.
Questions people ask
- Is Apache Druid or BigQuery better?
- Neither clearly leads. Apache Druid starts at Free and BigQuery at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Apache Druid or BigQuery?
- Apache Druid starts at Free and BigQuery at Free.
- Does Apache Druid or BigQuery run on more platforms?
- Apache Druid runs on Docker, Kubernetes, Native deployment (Java-based). BigQuery runs on Web, Cloud API.
- Can I use Apache Druid for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Apache Druid best used for?
- Apache Druid is most often used for real-time analytics platforms ingesting millions of events per second from streaming sources, applications requiring sub-second queries over high-cardinality datasets (billions to trillions of rows), time-series and event analysis at massive scale with columnar storage efficiency. Of those, real-time analytics platforms ingesting millions of events per second from streaming sources and applications requiring sub-second queries over high-cardinality datasets (billions to trillions of rows) are not what BigQuery is typically brought in for.
- What can Apache Druid do that BigQuery cannot?
- Apache Druid covers Real-time Ingestion, Sub-second Queries, Column-oriented Storage, Streaming Integration. BigQuery covers Serverless Architecture, Petabyte Scale, Real-time Analytics, Machine Learning.
Answered from the vendors’ own pages
BigQuery: How is BigQuery priced?
BigQuery charges $5 per terabyte of data processed in on-demand queries. Storage is billed separately: active storage is charged per GB, and data inactive for 90+ days moves to long-term storage at reduced rates.
SourceBigQuery: What is BigQuery's architecture?
BigQuery separates compute and storage, using Google's Colossus for distributed storage and Borg for computation, allowing independent scaling of each.
Source