Google Cloud Bigtable vs Amazon MemoryDB

Google Cloud Bigtable9.0Visit Amazon MemoryDB8.7Visit

Higher score Google Cloud Bigtable #3 in Key-Value Databases 9.0/10 10-day trial Free trial✓ 3 of 3 features Visit Google Cloud

vs

Amazon MemoryDB #6 in Key-Value Databases 8.7/10 Paid ✓ 3 of 3 features Try Amazon MemoryDB

• Google Cloud Bigtable fits best

  Large-scale analytical and wide-column workloads

• Amazon MemoryDB fits best

  Durable managed Redis or Valkey workloads

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Side by side

Feature	Google Cloud Bigtable 9.0/10 Visit ↗	Amazon MemoryDB 8.7/10 Visit ↗
At a glance
Editor score	9.0	8.7
Ranking	#3 in Key-Value Databases	#6 in Key-Value Databases
Best for	Large-scale analytical and wide-column workloads	Durable managed Redis or Valkey workloads
Pricing model	Paid	Paid
Starting price	$0.65/device usage-based	$0.20/GB usage-based
Free plan	—	—
Free trial	10 days	—
Deployment	Cloud	Cloud
Platforms	Web	Web
Integrations	8 integrations	7 integrations
Features Google Cloud Bigtable 3/3 · Amazon MemoryDB 3/3
TTL support	✓	✓
Clustering support	✓	✓
Multi-region support	✓	✓
Specs
Deployment model	Cloud	Cloud
Maximum value size	100 MB	Not checked yet
Persistence modes	Both	Both
Supported protocols	gRPC, REST/HTTP, Apache HBase API, Apache Cassandra API, GoogleSQL	Valkey Cluster protocol; Redis OSS Cluster protocol; HTTPS
Our review
Pros	Supports key-value and wide-column data models at scale Offers autoscaling, replication, backups, and SQL querying Connects with BigQuery, Dataflow, Spark, Vertex AI, and LangChain	Multi-AZ transactional-log durability with automatic failover JSON documents, vector search, and active-active multi-Region replication TLS, AWS KMS encryption, ACLs, and IAM-based access controls
Cons	No perpetual free plan Node-hour pricing can be relatively high Cloud deployment may not suit teams needing other models	No free plan; MemoryDB is paid-only On-demand charges vary by node type and usage Multi-Region deployments do not support TTL
Our verdict	Google Cloud Bigtable is a managed NoSQL database for high-throughput, low-latency applications built around key-value and wide-column data models. It is aimed at large datasets and workloads such as time-series data, operational… Read the review →	Amazon MemoryDB is a fully managed, durable in-memory key-value database for applications that need low-latency reads, fast writes, high throughput, and data durability. It is compatible with Valkey and Redis OSS data structures, commands,… Read the review →

Strengths and trade-offs

• Google Cloud Bigtable — where it wins

  • Supports key-value and wide-column data models at scale
  • Offers autoscaling, replication, backups, and SQL querying
  • Connects with BigQuery, Dataflow, Spark, Vertex AI, and LangChain

  Where it doesn't

  • No perpetual free plan
  • Node-hour pricing can be relatively high
  • Cloud deployment may not suit teams needing other models

• Amazon MemoryDB — where it wins

  • Multi-AZ transactional-log durability with automatic failover
  • JSON documents, vector search, and active-active multi-Region replication
  • TLS, AWS KMS encryption, ACLs, and IAM-based access controls

  Where it doesn't

  • No free plan; MemoryDB is paid-only
  • On-demand charges vary by node type and usage
  • Multi-Region deployments do not support TTL

• Google Cloud Bigtable9.0/10 · 10-day trial

  A scalable Bigtable service for analytical workloads, with broad integrations and usage-based pricing.

  Visit Google CloudFull verdict →
• Amazon MemoryDB8.7/10 · Paid

  A durable Redis- and Valkey-compatible service for low-latency, scalable workloads.

  Try Amazon MemoryDBFull verdict →