BigQuery vs Bigtable
Both are from Google. The names are so close and quite confusing, but they are totally different products.
(Note that Bigtable is NOT styled as BigTable, though the Q in BigQuery is in uppercase.)
Different use cases
- BigQuery is a data warehouse. SQL. Primarily used for offline analytics. Optimized for large-scale, ad-hoc SQL-based analysis and reporting.
- Bigtable is a wide-column database. NoSQL. Primarily used for online serving. Optimized for low latency, high throughput.
Both offered on Google Cloud Platform
- BigQuery is a service on GCP. It was developed from a Google internal query system called Dremel.
- Bigtable is the name of the database, GCP offers a version of it called Cloud Bigtable.
Competitors
- BigQuery: AWS Redshift, Snowflake, and other data warehouses.
- Bigtable: HBase, Cassandra (actually these open-source projects are based on the published Bigtable design).
Popularity
BigQuery is probably the most popular GCP product.
On DB-Engine ranking (https://db-engines.com/en/ranking):
- BigQuery is ranked 20+ and trending upwards;
- Bigtable is ranked 80+; do not expect it to rise up though, it is being replaced by Spanner.
Recommended ReadingSponsored
Versus
- 32-bit vs 64-bit
- AES vs RSA
- Agent vs Agentless
- Annotations vs Decorators
- Terraform vs Ansible
- BASH vs ZSH
- BigQuery vs Bigtable
- Block Storage vs File Storage vs Object Storage
- Canvas vs SVG
- cgroupfs vs systemd
- Constructor vs Init() vs Factory
- Container Image vs Helm Chart vs OCI Bundle
- Containers vs Virtual Machines (VMs)
- C vs C++
- Java vs C++
- Rust vs C++
- crictl vs ctr
- Dagger vs Guice
- DMA vs RDMA
- DOM vs Virtual DOM vs Shadow DOM
- DQL vs DDL vs DCL vs DML
- eBPF vs Sidecar
- Flux vs Redux
- Full Disk Encryption vs Partition Encryption
- Gatekeeper vs OPA
- Google vs Open Source
- Why MCP uses JSON-RPC 2.0 instead of grpc
- gRPC vs OpenAPI
- gtag.js vs Google Tag Manager (GTM)
- Versus
- Kotlin vs Java
- Jetty vs Netty
- .js vs .jsx vs .ts vs .tsx
- Kata Containers vs KubeVirt
- Linux Namespace vs Kubernetes Namespace
- Linux vs BSD
- LLVM vs JVM
- Data Mining vs Machine Learning vs Artificial Intelligence vs Data Science
- Managed Kubernetes vs Self-managed Kubernetes
- Management Plane vs Control Plane vs Data Plane
- Microcontroller vs Microprocessor vs Computer
- MMU vs IOMMU
- Single-tenant vs Multi-tenant vs Multi-single-tenant
- Multithreading vs Multiprocessing vs Distributed Systems
- Node.js vs Erlang
- OCI Image vs Docker Image
- OCI vs CRI
- OpenSSH vs OpenSSL
- Pass-by-value vs Pass-by-reference
- Podman vs nerdctl
- POSIX vs SUS vs LSB
- Private Key vs Public Key vs Certificate
- Proto Edition 2024 vs Proto Edition 2023
- Proto2 vs Proto3 vs Proto Editions
- Message Queue vs PubSub
- React vs Flutter vs Angular
- REST vs SOAP
- RSA vs ECDSA
- select vs. poll vs. epoll
- SLI vs SLO vs SLA
- Spanner vs Bigtable
- Static Site Generation vs Server-side Rendering vs Client-side Rendering
- Stack based VM vs Register based VM
- Stateless vs Stateful
- Strong Consistency vs Eventual Consistency
- stubs vs mocks vs fakes
- Subroutines vs Coroutines vs Generators
- Software Engineer vs Site Reliability Engineer
- Symlinks vs Hard Links
- JAX vs Tensorflow
- Tensorflow vs PyTorch
- Terminal vs Shell
- Throttling vs Load Shedding
- Unix Domain Sockets vs Network Sockets
- Unix Domain Sockets vs Shared Memory
- URI vs URN vs URL vs URC
- Valkey vs Redis vs Memcached
- Vi vs Vim vs gVim vs Neovim
- WAL vs rollback journal

