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Databases · head to head

Apache Hadoop vs RisingWave

Apache Hadoop logo

Apache Hadoop

Databases

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

From
Free
Free plan
Yes
Visit Apache HadoopFull review
RisingWave logo

RisingWave

Databases

Streaming database that maintains incremental materialised views in SQL instead of Flink jobs

From
Free
Free plan
Yes
Visit RisingWaveFull review

The short version

  • Apache Hadoop is free; RisingWave starts at $0.227/mo.
  • Only Apache Hadoop lists HDFS federation and high availability; only RisingWave lists SQL materialised views.
  • Prices and features on this page were last checked on 13 November 2026.

Where they differ

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

Attributes where Apache Hadoop and RisingWave differ
AttributeApache HadoopRisingWave
Pricing modelOpen-sourcePer RisingWave Unit hour
PlatformsWebLinux, Self-hosted, Web

Identical on both: starting price (Free), free tier (Yes), category (Databases).

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 RisingWave

  • SQL materialised views
  • Postgres wire compatibility
  • Object storage state
  • Source connectors
  • Sink connectors
  • Iceberg tables
  • Watermarks and windowing
  • User defined functions

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 RisingWave
  • Running Spark or Flink under YARN on hardware you already own, using HDFS as the storage layernot RisingWave
  • Keeping long-lived regulated archives on infrastructure entirely within your own data centres and legal jurisdictionnot RisingWave
  • Maintaining legacy Hive and MapReduce workloads during a staged migration to a lakehouse or cloud platformnot RisingWave

RisingWave

  • A team with Kafka topics that needs continuously fresh aggregates for a dashboard without standing up a Flink clusternot Apache Hadoop
  • A fraud or risk team maintaining rolling counters and joins across event streams expressed as SQL viewsnot Apache Hadoop
  • A company doing Postgres CDC into a real-time denormalised view for search or servingnot Apache Hadoop
  • An analytics group that wants streaming results landed directly into Apache Iceberg without a separate writer jobnot 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

RisingWave

  • Anything that does not fit SQL, such as custom windowing, complex event processing or heavy stateful logic, still needs Flink, so RisingWave often adds a system rather than removing one
  • The Apache 2.0 community edition excludes premium features behind a licence key, and which capabilities sit on which side of that line moves between releases, so a self-hosted plan can be invalidated by an upgrade
  • Long-running materialised views accumulate state in object storage, and cost and recovery time grow with retention in ways that are hard to forecast before you are in production
  • The Postgres compatibility is protocol level; it is not a transactional Postgres and using it as a general purpose database, with point updates or high write concurrency, goes badly
  • It is a comparatively young venture-funded project competing with Flink, Materialize and warehouse-native streaming, and the ecosystem of connectors, operators and third-party expertise is much thinner

Pricing, plan by plan

Apache Hadoop

Free

No published plan breakdown. See the Apache Hadoop review.

RisingWave

Free
  • Community EditionFree
    • Apache 2.0 licence, self-hosted
    • Core streaming engine and connectors
    • Premium features excluded and require a licence key
  • Cloud Basic$0.227/hour
    • Billed per RisingWave Unit hour
    • Hosted on AWS, GCP or Azure
    • Capped at 64 cores
  • Cloud ProOn request
    • No core limit
    • Bring your own cloud option
    • Premium features included
  • Self-managed EnterpriseOn request
    • On premises or Kubernetes
    • Premium features unlocked by licence
    • Annual contract with SLA

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 RisingWave if

  • You need sql materialised views.
  • You want to start without paying.
  • You work on Linux, Self-hosted, Web.
  • You also want postgres wire compatibility.
RisingWave review

Questions people ask

Is Apache Hadoop or RisingWave better?
Neither clearly leads. Apache Hadoop starts at Free and RisingWave at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Hadoop or RisingWave?
Apache Hadoop starts at Free and RisingWave at Free.
Does Apache Hadoop or RisingWave run on more platforms?
Apache Hadoop runs on Web. RisingWave runs on Linux, Self-hosted, Web.
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 RisingWave is typically brought in for.
What can Apache Hadoop do that RisingWave cannot?
Apache Hadoop covers HDFS, YARN, MapReduce, HDFS federation and high availability. RisingWave covers SQL materialised views, Postgres wire compatibility, Object storage state, Source connectors.

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.

RisingWave: Is RisingWave open source?

The community edition is Apache 2.0 and self-hostable, but a set of premium features requires a paid licence key.

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.

RisingWave: What does the cloud cost?

It starts at 0.227 US dollars per RisingWave Unit hour on the Basic tier, which is capped at 64 cores.

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.

RisingWave: Does it replace Flink?

For SQL-expressible transformations, often yes. For custom stateful processing and complex event handling, no.

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.

RisingWave: Can I query it like Postgres?

Yes over the Postgres wire protocol, but it is an analytical streaming engine, not a transactional database.

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.

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