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Apache Hadoop vs Envoy

Apache Hadoop logo

Apache Hadoop

Technology

The original open source framework for distributed storage and batch processing on commodity servers, now largely a legacy platform.

From
Free
Rated
-
Full reviewWebsite
Envoy logo

Envoy

Technology

A high-performance L7 proxy written in C++ that is configured by an API rather than a config file, and is usually deployed under a control plane.

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Apache Hadoop the free vendor distributions no longer exist: Cloudera's CDH and Hortonworks' HDP have reached end of support and the successor CDP is subscription-only, so running Hadoop without paying now means assembling, testing and security-patching Apache releases yourself.; Envoy the configuration surface is very large and hand-written bootstrap YAML runs to hundreds of lines for routing that Nginx expresses in twenty, which is why nearly every production deployment sits under a control plane and inherits that control plane's constraints as well.
  • They diverge on capability: Apache Hadoop covers HDFS, Envoy covers xDS dynamic configuration.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

Only the attributes on which Apache Hadoop and Envoy actually diverge.

Attributes where Apache Hadoop and Envoy differ
AttributeApache HadoopEnvoy

Identical on both: starting price (Free), pricing model (open-source), free tier (Yes), platforms (Web), user rating (Not yet rated), category (Technology).

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 Apache Hadoop

  • HDFS
  • YARN
  • MapReduce
  • HDFS federation and high availability
  • Kerberos security
  • Rack awareness
  • S3A and object store connectors
  • Ecosystem compatibility

Only in Envoy

  • xDS dynamic configuration
  • Protocol breadth
  • Filter chain architecture
  • Observability by default
  • Outlier detection
  • Traffic shaping
  • mTLS termination and origination
  • Hot restart

What people use each for

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

Apache Hadoop

  • Operating an existing multi-petabyte on-premises estate where data residency or egress costs rule out moving to cloud object storagenot Envoy
  • Running Spark or Flink under YARN on hardware you already own, using HDFS as the storage layernot Envoy
  • Keeping long-lived regulated archives on infrastructure entirely within your own data centres and legal jurisdictionnot Envoy
  • Maintaining legacy Hive and MapReduce workloads during a staged migration to a lakehouse or cloud platformnot Envoy

Envoy

  • Acting as the data plane under a service mesh or Gateway API implementation, which is how the overwhelming majority of deployments use itnot Apache Hadoop
  • An edge or API gateway that needs per-route retry budgets, circuit breaking and outlier detection rather than round-robin proxyingnot Apache Hadoop
  • Migrating traffic between service versions or between a monolith and its replacement, using weighted splits and shadow trafficnot Apache Hadoop
  • Standardising observability across a polyglot estate, so that latency, error rates and tracing look the same regardless of the language a service is written innot Apache Hadoop

Where each one falls short

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

Apache Hadoop

  • The free vendor distributions no longer exist: Cloudera's CDH and Hortonworks' HDP have reached end of support and the successor CDP is subscription-only, so running Hadoop without paying now means assembling, testing and security-patching Apache releases yourself.
  • HDFS couples storage to compute, so adding capacity means buying whole nodes with CPU and memory you may not need, and the entire industry moved to object storage precisely because it lets the two be bought separately.
  • The NameNode holds all filesystem metadata in memory, so a cluster with tens of millions of small files exhausts heap long before it exhausts disk, and the remedy is a file compaction job that somebody has to write, schedule and own indefinitely.
  • Operating it is a distinct specialism covering Kerberos, YARN queue tuning, JVM garbage collection and the compatibility matrix between Hive, HBase, Ranger, Oozie and the core, and an upgrade touches all of them at once rather than one at a time.
  • MapReduce is maintained for compatibility rather than actively developed, and new work goes to Spark or Flink, so a job written against MapReduce today is written against an API that will not gain anything further.
  • Hiring is against you: the talent pool has moved to cloud data platforms over the past decade, so a Hadoop estate increasingly depends on a small number of individuals, which makes it a succession risk before it is a technical one.

Envoy

  • The configuration surface is very large and hand-written bootstrap YAML runs to hundreds of lines for routing that Nginx expresses in twenty, which is why nearly every production deployment sits under a control plane and inherits that control plane's constraints as well.
  • xDS is the real API and it is not stable in the comfortable sense; the v2 API set was removed outright, resource types continue to be deprecated, and your control plane and Envoy binaries have to be upgraded roughly in step or the proxies stop accepting configuration.
  • Extending it properly means writing a C++ filter and building and maintaining your own Envoy binary; the alternatives are Lua, which adds per-request overhead, and proxy-wasm, whose ABI has remained effectively experimental for years with a real performance cost.
  • At sidecar density the per-proxy memory and CPU footprint is a measurable share of cluster capacity, since thousands of workloads each carry a full proxy, and this is precisely the cost that has pushed mesh projects towards node-level or ambient architectures.
  • There is no single vendor selling support for Envoy itself; you get the community plus control-plane vendors such as Solo.io and Tetrate, so an Envoy-level production bug is your own engineers in a C++ codebase unless a support contract happens to cover it.
  • Diagnosing why a request got a particular response involves reading config dumps, the stats endpoint and the RESPONSE_FLAGS codes in access logs rather than a readable error, which is a specific skill you must hire or spend months growing.

Pricing, plan by plan

Apache Hadoop

Free

No published plan breakdown. See the Apache Hadoop review.

Envoy

Free

No published plan breakdown. See the Envoy review.

Which should you pick?

Choose Apache Hadoop if

  • You need hdfs.
  • You want to start without paying.
  • You also want yarn.
Apache Hadoop review

Choose Envoy if

  • You need xds dynamic configuration.
  • You want to start without paying.
  • You also want protocol breadth.
Envoy review

Questions people ask

Is Apache Hadoop or Envoy better?
Neither clearly leads. Apache Hadoop starts at Free and Envoy at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Hadoop or Envoy?
Apache Hadoop starts at Free and Envoy at Free.
Does Apache Hadoop or Envoy run on more platforms?
Both run on Web, so platform support will not decide this one for you.
Can I use Apache Hadoop for free?
Both have a free tier, so you can try either at no cost before committing.
What is Apache Hadoop best used for?
Apache Hadoop is most often used for operating an existing multi-petabyte on-premises estate where data residency or egress costs rule out moving to cloud object storage, running spark or flink under yarn on hardware you already own, using hdfs as the storage layer, keeping long-lived regulated archives on infrastructure entirely within your own data centres and legal jurisdiction, maintaining legacy hive and mapreduce workloads during a staged migration to a lakehouse or cloud platform. Of those, operating an existing multi-petabyte on-premises estate where data residency or egress costs rule out moving to cloud object storage and running spark or flink under yarn on hardware you already own, using hdfs as the storage layer are not what Envoy is typically brought in for.
What can Apache Hadoop do that Envoy cannot?
Apache Hadoop covers HDFS, YARN, MapReduce, HDFS federation and high availability. Envoy covers xDS dynamic configuration, Protocol breadth, Filter chain architecture, Observability by default.

Answered from the vendors’ own pages

Apache Hadoop: Is Hadoop dead?

No, but it is legacy. Large on-premises HDFS estates still run and are still supported, and Spark and Flink still run on YARN. What has ended is Hadoop as a default choice for new platforms, which now start on object storage.

Envoy: Should I run Envoy on its own, or under a control plane?

Almost always under one. Directly authoring xDS or static bootstrap configuration is viable for a handful of routes and becomes unmanageable beyond that. Envoy Gateway, Istio, Contour, Gloo and Consul all exist to generate that configuration for you.

Apache Hadoop: Can I still get a free packaged distribution?

Not a maintained one. CDH and HDP reached end of support and Cloudera's CDP is a paid subscription. The remaining free route is building and patching Apache releases yourself, which is a real engineering commitment.

Envoy: How does it compare with Nginx or HAProxy?

Envoy is dynamically configured over an API and instrumented far more heavily; Nginx and HAProxy are faster to configure and lighter for straightforward reverse proxying. If you never need to change routing without a reload, Envoy is more machinery than the problem requires.

Apache Hadoop: Do I need Hadoop to run Spark?

No. Spark runs standalone, on Kubernetes and on managed cloud services, and reads object storage directly. Many Spark deployments include Hadoop client libraries for the filesystem connectors without running a Hadoop cluster at all.

Envoy: What does it cost?

Nothing to licence; it is Apache 2.0 and there is no paid edition. The cost is engineering time and, for most organisations, a commercial control plane or cloud service that packages it.

Apache Hadoop: What replaced HDFS?

Object storage, typically S3 or a compatible system, combined with an open table format such as Apache Iceberg or Delta Lake. Apache Ozone exists as an object store within the Hadoop ecosystem for organisations staying on-premises.

Envoy: Can I write extensions without C++?

You can write Lua filters or proxy-wasm modules in Rust, Go, C++ or AssemblyScript. Both carry per-request overhead compared with a native filter, and the Wasm path has been slower to stabilise than the project originally projected.

Apache Hadoop: Is it cheaper than the cloud?

It can be at multi-petabyte scale with steady, predictable utilisation, particularly where egress charges would be large. Include the staffing cost honestly, because the specialist operators a Hadoop cluster requires are scarce and therefore expensive.

Envoy: Is it a CNCF project?

Yes, it is a graduated CNCF project licensed under Apache 2.0, which means the trademark and governance sit with the foundation rather than with Lyft or any vendor.

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