Head-to-head · Wide-Column Databases
Apache Cassandra vs Google Cloud Bigtable
Apache Cassandra leads on 0 checks, Google Cloud Bigtable on 0, and 4 are even. Who comes out ahead on the 4 yes/no, price and count checks where we have data for both products. The editor score weighs everything else too.
Our verdict
- Highest scoreApache Cassandra · 9.3/10
- Free trialonly Google Cloud Bigtable
- Most featuresApache Cassandra · 3 of 3
Apache Cassandra scores higher on our rubric for wide-column databases: 9.3 against 9.1 out of 10; our editors rank them #1 and #2.
Apache Cassandra is the better fit for mature self-hosted Cassandra-compatible deployments. Google Cloud Bigtable is the better fit for managed wide-column workloads with rich cloud integrations.
- Apache Cassandra fits best
Mature self-hosted Cassandra-compatible deployments
- Google Cloud Bigtable fits best
Managed wide-column workloads with rich cloud integrations
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Side by side
| Feature | Apache Cassandra 9.3/10 Visit ↗ | Google Cloud Bigtable 9.1/10 Visit ↗ |
|---|---|---|
| At a glance | ||
| Editor score | 9.3 | 9.1 |
| Ranking | #1 in Wide-Column Databases | #2 in Wide-Column Databases |
| Best for | Mature self-hosted Cassandra-compatible deployments | Managed wide-column workloads with rich cloud integrations |
| Pricing model | Free | Paid |
| Starting price | Open source | $0.65/device usage-based |
| Free plan | Not checked yet | — |
| Free trial | — | 10 days |
| Deployment | Self-hosted, Desktop | Cloud |
| Platforms | Web, Windows, macOS, Linux | Web |
| Features Apache Cassandra 3/3 · Google Cloud Bigtable 0/3 | ||
| Multi-region support | ✓ (best) | Not checked yet |
| Transaction support | ✓ (best) | Not checked yet |
| Horizontal scaling | ✓ (best) | Not checked yet |
| Specs | ||
| Deployment model | Self_hosted | Not checked yet |
| Query interface | Cql | Not checked yet |
| Consistency controls | Tunable | Not checked yet |
| Maximum row size | Not checked yet | Not checked yet |
| Our review | ||
| Pros |
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| Cons |
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| Our verdict | Apache Cassandra is an open-source, distributed NoSQL database built around a partitioned wide-column storage model. It is aimed at teams managing self-hosted workloads that need high-volume reads and writes, large datasets, fault… Read the review → |
Google Cloud Bigtable is a managed NoSQL database for high-throughput, low-latency applications built on key-value and wide-column data models. It is aimed at large datasets across time-series, operational analytics, machine learning, IoT,… Read the review → |
Strengths and trade-offs
Apache Cassandra — where it wins
- Partitioned wide-column model with CQL query access
- Datacenter replication and tunable consistency controls
- Horizontal scaling by adding nodes
Where it doesn't
- Self-managed deployment requires infrastructure ownership
- CQL is the primary query interface
- Desktop deployment uses Docker on supported operating systems
Google Cloud Bigtable — where it wins
- Autoscaling, replication, backups, and expiration controls
- Supports GoogleSQL, HBase, Cassandra, gRPC, and REST/HTTP
- Integrates with BigQuery, Dataflow, Spark, Vertex AI, and LangChain
Where it doesn't
- Usage-based pricing includes node, storage, and network charges
- No perpetual free plan; the free trial starts at 10 days
- Cloud deployment may not suit workloads requiring other models
- Apache Cassandra9.3/10 · Open source
A mature self-hosted Cassandra-compatible database for distributed, high-volume workloads.
Try Apache CassandraFull verdict → - Google Cloud Bigtable9.1/10 · 10-day trial
A scalable managed database for wide-column workloads with deep Google Cloud integration.
Visit Google CloudFull verdict →
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- Apache Cassandra vs Alibaba Cloud Lindorm
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- Apache Cassandra vs Apache HBase
- Apache Cassandra vs Cloudera Operational Database
- Apache Cassandra vs DataStax Astra DB
- Google Cloud Bigtable vs Azure Cosmos DB for Apache Cassandra
- Google Cloud Bigtable vs Alibaba Cloud Lindorm
All Wide-Column databases comparisons → · Full ranking →
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Last updated · How we research and update






