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Database & Data Management · head to head

Amazon Aurora vs Datadog Logs

Amazon Aurora logo

Amazon Aurora

Database & Data Management

MySQL and PostgreSQL-compatible relational database built for the cloud

From
Free
Rated
-
Full reviewWebsite
Datadog Logs logo

Datadog Logs

Log Management

Log Management and Analytics

From
$0.1/per GB ingested per month
Rated
-
Full reviewWebsite

The short version

  • Only Amazon Aurora has a free tier, so it costs nothing to try first.
  • Each has a real cost: Amazon Aurora aurora requires AWS ecosystem knowledge and integration with other AWS services; Datadog Logs complex, multi-tiered pricing model based on ingestion, indexing, and storage; can become expensive at scale
  • They diverge on capability: Amazon Aurora covers MySQL/PostgreSQL Compatible, Datadog Logs covers Log ingestion.

Where they differ

Only the attributes on which Amazon Aurora and Datadog Logs actually diverge.

Attributes where Amazon Aurora and Datadog Logs differ
AttributeAmazon AuroraDatadog Logs
Starting priceFree$0.1/per GB ingested per month
Free tierYesNo
PlatformsAWS CloudCloud (AWS, Azure, Google Cloud, Oracle Cloud)
CategoryDatabase & Data ManagementLog Management
Founded20062010

Identical on both: pricing model (usage-based), user rating (Not yet rated).

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 Amazon Aurora

  • MySQL/PostgreSQL Compatible
  • 5x MySQL Performance
  • Auto-scaling Storage
  • Global Database
  • Serverless v2
  • Multi-master
  • Fault Tolerant
  • AWS Lambda

Only in Datadog Logs

  • Log ingestion
  • Full-text search
  • Custom dashboards
  • Log-based metrics
  • API
  • Webhooks
  • REST
  • Api support

Both cover

  • Web support

What people use each for

The jobs each tool is most often brought in to do.

Amazon Aurora

  • Transaction processingnot Datadog Logs
  • Data storagenot Datadog Logs
  • Application backendnot Datadog Logs
  • Reportingnot Datadog Logs
  • Data analyticsnot Datadog Logs

Datadog Logs

  • Centralised log aggregation and analysisnot Amazon Aurora
  • Multi-source log correlation with metrics and tracesnot Amazon Aurora
  • Root cause analysis and troubleshootingnot Amazon Aurora
  • Security monitoring and threat detectionnot Amazon Aurora

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Amazon Aurora

  • Aurora requires AWS ecosystem knowledge and integration with other AWS services
  • Pricing can become expensive with high-traffic applications using many read replicas
  • Limited support for non-relational data types compared to NoSQL alternatives

Datadog Logs

  • Complex, multi-tiered pricing model based on ingestion, indexing, and storage; can become expensive at scale
  • Ingestion pricing of $0.10/GB can accumulate rapidly for high-volume logging environments

Pricing, plan by plan

Amazon Aurora

Free
  • Serverless v2$0.12/hour
    • Auto-scaling
    • Pay per ACU
    • Instant scaling
  • Provisioned$29/month
    • Dedicated instances
    • Predictable performance
    • Reserved capacity

Datadog Logs

$0.1/per GB ingested per month

No published plan breakdown. See the Datadog Logs review.

Which should you pick?

Choose Amazon Aurora if

  • You need mysql/postgresql compatible.
  • You want to start without paying.
  • You work on AWS Cloud.
  • You also want 5x mysql performance.
Amazon Aurora review

Choose Datadog Logs if

  • You need log ingestion.
  • You work on Cloud (AWS, Azure, Google Cloud, Oracle Cloud).
  • You also want full-text search.
Datadog Logs review

Questions people ask

Is Amazon Aurora or Datadog Logs better?
Neither clearly leads. Amazon Aurora starts at Free and Datadog Logs at $0.1/per GB ingested per month, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Amazon Aurora or Datadog Logs?
Amazon Aurora has a free tier; the other does not. Paid plans start at Free for Amazon Aurora and $0.1/per GB ingested per month for Datadog Logs.
Does Amazon Aurora or Datadog Logs run on more platforms?
Amazon Aurora runs on AWS Cloud. Datadog Logs runs on Cloud (AWS, Azure, Google Cloud, Oracle Cloud).
Can I use Amazon Aurora for free?
Yes. Amazon Aurora has a free tier, so you can try it without paying. Datadog Logs starts at $0.1/per GB ingested per month.
What is Amazon Aurora best used for?
Amazon Aurora is most often used for transaction processing, data storage, application backend, reporting. Of those, transaction processing and data storage are not what Datadog Logs is typically brought in for.
What can Amazon Aurora do that Datadog Logs cannot?
Amazon Aurora covers MySQL/PostgreSQL Compatible, 5x MySQL Performance, Auto-scaling Storage, Global Database. Datadog Logs covers Log ingestion, Full-text search, Custom dashboards, Log-based metrics. Both handle Web support.

Answered from the vendors’ own pages

Amazon Aurora: Is Amazon Aurora compatible with MySQL and PostgreSQL?

Yes, Amazon Aurora offers MySQL and PostgreSQL compatibility with full compatibility to their open-source counterparts, allowing you to migrate existing databases with standard tools.

Source
Amazon Aurora: What uptime SLA does Amazon Aurora provide?

Aurora is designed for up to 99.99% single-region uptime and 99.999% multi-region uptime with automatic failover.

Source
Amazon Aurora: How much does Amazon Aurora cost?

Aurora uses serverless, usage-based pricing where you pay only for consumed capacity. Typical pricing ranges from $50-70 per month for minimal setups to $400-600 per month for small production clusters.

Source
Amazon Aurora: Can Amazon Aurora scale automatically?

Yes, Aurora automatically scales to match workload demands without performance degradation, supporting both read and write scaling.

Source
Amazon Aurora: How many read replicas does Aurora support?

Aurora supports up to 15 low-latency read replicas for distributing read traffic across your application.

Source
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