AWS OpenSearch vs. ElasticSearch on EKS: Which One’s Right for Your Team?

You’ve got data, and you need a powerful search engine to make sense of it. But should you go with AWS OpenSearch, the fully managed solution, or flex your control muscles with ElasticSearch on EKS? It’s not just a matter of costs and complexity—features and workload patterns play a huge role too.

This article will break down everything you need to know, from pricing to personnel hours, features, and when you should consider using spot instances or Serverless OpenSearch.

Let’s dive in!

AWS OpenSearch: The Managed, Simpler Option—But With Fewer Features

AWS OpenSearch gives you the benefit of full management by AWS. You don’t need to worry about scaling, patching, or backups. AWS handles that for you, so you can focus on searching and indexing. But simplicity comes with some trade-offs—especially in terms of features compared to ElasticSearch.

Why Choose AWS OpenSearch?

• Easy Setup: You can get a cluster up and running in minutes—no infrastructure worries.
• Managed Scaling: AWS handles auto-scaling based on traffic, so you don’t need to intervene manually.
• AWS Integration: OpenSearch works seamlessly with AWS services like VPC, S3, and CloudWatch.

What’s Missing in AWS OpenSearch?

• No APM (Application Performance Monitoring): ElasticSearch offers APM, which gives you insights into application performance, spotting bottlenecks and latency issues in real-time. OpenSearch doesn’t have this feature.
• Limited Machine Learning: ElasticSearch comes with built-in machine learning features for things like anomaly detection and forecasting. OpenSearch has some similar features, but they’re not as mature.
• Smaller Ecosystem: While OpenSearch has OpenSearch Dashboards (a fork of Kibana), the overall ecosystem and tooling are smaller than ElasticSearch’s full suite (Kibana, Beats, Logstash).

AWS OpenSearch Example Costs:

Let’s assume you’re running a 3-node cluster, 24/7, with 300 GB of data:

• 3 r5.large nodes (on-demand): $1,028/month.
• Storage (300 GB EBS): $30/month.
• Engineer Time: 2 hours/month, or $150.

Total: $1,208/month for a hands-off solution with fewer advanced features.

ElasticSearch on EKS: Full Control with All the Features

ElasticSearch on EKS gives you complete control and access to the full Elastic Stack, including APM, machine learning, and data pipelines. This option fits best for teams already using Kubernetes and those who need advanced features for their search workloads.

Why Choose ElasticSearch on EKS?

• Full Elastic Stack: You get Kibana, APM, machine learning, and data processing pipelines with Logstash and Beats.
• APM for Monitoring: ElasticSearch’s Application Performance Monitoring (APM) gives you real-time insights into app performance, helping you find performance bottlenecks and latency issues.
• Complete Customization: Full control over node configuration, scaling, and plugins. This is perfect for teams that need to tweak their search infrastructure.

ElasticSearch on EKS Example Costs:

Let’s assume the same 3-node setup, but now you’re managing everything with EKS:

• 3 r5.large nodes (on-demand): $1,028/month.
• EKS Control Plane: $72/month.
• Storage (300 GB EBS): $30/month.
• Engineer Time: 8 hours/month, or $600.

Total: $1,730/month for full control and all the features, but with more hands-on management.

ElasticSearch on EKS with Spot Instances: Cutting Costs, Keeping Features

ElasticSearch on EKS gets even more cost-effective when you use spot instances for non-critical nodes. Spot instances give you up to 90% off regular pricing but come with the risk that AWS may reclaim them at any time. They’re perfect for master or client nodes, or even data nodes if you’re okay with occasional interruptions.

Why Spot Instances Are a Great Fit:

• Huge Savings: You can save significantly by using spot instances for nodes that can handle interruptions.
• All the Features: Even with spot instances, you still get the full suite of ElasticSearch features—APM, machine learning, Beats, and more.

ElasticSearch on EKS with Spot Instances Costs:

Let’s apply spot pricing to the 3-node setup:

• 3 r5.large nodes (spot pricing): $414/month (spot pricing is around 60% cheaper than on-demand).
• EKS Control Plane: $72/month.
• Storage (300 GB EBS): $30/month.
• Engineer Time: Still 8 hours/month, or $600.

Total: $1,116/month—a $600 savings compared to on-demand pricing.

Serverless OpenSearch: Flexible, But Watch Out for Costs

AWS also offers Serverless OpenSearch, which is completely hands-off, scaling up and down based on usage. But while serverless is great for bursty, unpredictable workloads, the costs can get out of control for heavy, consistent use.

Why Serverless OpenSearch Might Work for You:

• No Infrastructure to Manage: AWS handles everything from scaling to backups.
• Great for Bursty Workloads: You only pay for the compute and storage you use, making it ideal for workloads that spike unpredictably.

When Serverless Costs Spiral Out of Control:

If your workload involves constant data ingestion and heavy querying, serverless can get expensive quickly.

Example: For 2 TB of data ingestion and 1,000 hours of query time per month:

• Data Ingestion: $204/month.
• Query Processing: $450/month.
• Storage (2 TB): $48/month.
• Engineer Time: 1 hour/month, or $75.

Total: $777/month. This seems reasonable, but if your workload grows, so will your costs. Compare this to the $1,730/month for ElasticSearch on EKS (on-demand). For constant, high-traffic workloads, serverless can become more expensive than you think.

Final Thoughts: Which Should You Choose?

• Choose AWS OpenSearch if:
  • You need a simple, managed solution that integrates with AWS services.
  • You don’t need APM or advanced machine learning features.
  • Your team has limited DevOps resources and wants minimal management overhead.
• Choose ElasticSearch on EKS if:
  • You need the full power of the Elastic Stack—including APM, machine learning, and more.
  • You’re already using Kubernetes and want full control over your cluster.
  • You’re willing to manage infrastructure yourself in exchange for more flexibility.
• Choose Serverless OpenSearch if:
  • Your workload is bursty and unpredictable.
  • You want to avoid managing any infrastructure.
  • You understand that for consistent, high-volume workloads, serverless may actually be more expensive.

The key to choosing the right solution lies in understanding your workload patterns, feature needs, and how much management time you’re willing to commit. If you need full control and advanced features, ElasticSearch on EKS is the winner. But for simple, managed solutions or bursty workloads, AWS OpenSearch or Serverless OpenSearch might be your best bet.