Apache Druid Consulting & Support

Apache Druid Consulting & Support for Enterprises

AceMQ engineers design segment and ingestion architecture for sub-second analytics at scale, and run the tiered storage strategies that keep that scale affordable. Every engagement is staffed by a named senior engineer who understands the coordinator, broker, historical, and middleManager roles as a system, not in isolation.

A senior engineer, not an SDR. No sales sequence attached.

Senior SMEs
11+
Emergency SLA
<15min
Customers
160+
Countries Served
26+

Without re-ingesting years of segments or replacing the query layerFor production incident cover, see AceMQ Apache Druid 24/7 support.

Customers

  • Microsoft
  • Henry Schein
  • Enbridge
  • Gojek

Partners

  • Broadcom
  • Redis
  • VMware Tanzu
  • OSSeva

The Problem

Why teams call us about Apache Druid

Eight Apache Druid problems that teams bring to AceMQ, from thousands of undersized segments and compaction that never reaches old intervals to stalled Kafka supervisors, full Historicals and saturated MiddleManager task slots. If one describes your week, that is where the review starts.

  1. 01

    Segments are far smaller than the target size and every query fans out across thousands of them

  2. 02

    Compaction tasks queue behind ingestion and never reach the older intervals

  3. 03

    Historicals are out of disk while the deep storage tier sits largely empty

  4. 04

    A Kafka supervisor stalled and the ingestion lag went unnoticed for days

  5. 05

    Queries scan every interval because the time filter is not being pushed down

  6. 06

    MiddleManager task slots saturate at peak and ingestion falls behind

  7. 07

    Rollup granularity was set at first ingest and no longer matches what analysts ask for

  8. 08

    The node count grew to solve a query latency problem that segment sizing would have fixed

A good fit if you run Apache Druid for real-time analytics in production and want senior engineers who understand the coordinator, broker, historical and middleManager roles as one system.

Not a fit for small teams with non-critical workloads. AceMQ is not a budget consultancy: we work with enterprises running business-critical and compliance-heavy Apache Druid.

Running Apache Druid in production? Get a quote from a senior engineer, answered within one hour.

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How it breaks, and the fix

What happens to Druid queries when a Historical node is lost?

When a Historical drops out, the segments it served must be loaded elsewhere. With one replica those segments are unavailable and queries return partial results. With two, the Broker routes to the surviving copies while the Coordinator re-replicates, if the remaining Historicals have disk to take them.

One lost Historical, segments at risk

One Broker and three Historicals in a tier, segments loaded from deep storage

Illustrative

  1. Every segment is loaded on two Historicals. The Broker fans queries out, and each Historical serves about half its disk and memory budget.

  2. Historical 2 drops out. Segments with a single replica become unavailable and queries return partial results. Historicals 1 and 3 run hot, and the Coordinator cannot reload the missing segments because the tier's disks are nearly full.

  3. Historical 2 rejoins, or free disk lets the Coordinator re-replicate its segments onto the others. Segment availability returns to 100 percent and load levels out across the tier.

Segments that never become queryable is a Druid incident AceMQ sees often, and a node loss exposes it. The cause is usually tier capacity or load rules: too few replicas, a full tier, or a period rule that no longer matches where queries land. The fix is capacity headroom per tier, replicas matched to the availability you need, compaction so fewer, larger segments reach each Historical, and alerts on unavailable segments rather than only on node health.

Our Services

Apache Druid Consulting & Services

AceMQ runs five Apache Druid service lines: segment and ingestion architecture, tiered storage and performance, migration from Elasticsearch and warehouses, managed operations and health checks. A senior engineer leads each one, and any of them can roll into 24/7 support with a 15-minute emergency SLA.

  • 01

    Druid Segment & Ingestion Architecture

    Segment granularity and rollup design determine both your query latency and your storage bill. We design them around your actual dimension cardinality and query patterns, not defaults.

    • Segment granularity and rollup design for sub-second real-time analytics
    • Kafka indexing service configuration for exactly-once streaming ingestion
    • Batch ingestion pipeline design — native batch and Hadoop-based — for historical backfill
    • Dimension and metric schema design balancing cardinality against query speed
  • 02

    Cluster Performance & Tiered Storage

    Tiered historical storage is what makes Druid affordable at scale — hot data on fast nodes, cold data on cheap ones. We design the tiering rules and query approach that keep both cost and latency in check.

    • Tiered historical storage design — hot, warm, cold — to control infrastructure cost at scale
    • Query performance tuning: topN vs. groupBy selection and approximate algorithms (HLL, theta sketches)
    • Coordinator and broker capacity planning across segment load and query concurrency
    • Compaction scheduling to control segment count and query fan-out
  • 03

    Migration from Elasticsearch & Data Warehouses

    Teams move to Druid when sub-second query latency at scale becomes the requirement Elasticsearch or a batch warehouse can't meet. We validate that requirement against a benchmark before committing to the migration.

    • Cost and latency-driven migration off Elasticsearch for sub-second aggregation queries
    • Schema redesign migrating from traditional data warehouses to Druid's segment model
    • Comparative benchmarking against ClickHouse to validate the right OLAP engine for your workload
    • Dual-cluster validation before production cutover
  • 04

    Managed Operations & 24/7 Support

    A Druid cluster has more moving parts than most databases — coordinator, overlord, broker, historical, middleManager — and a failure in any one degrades the whole system differently. We monitor them as a system.

    • Cluster role monitoring across coordinator, overlord, broker, historical, and middleManager
    • Segment balancing and load rule enforcement across historical tiers
    • 24/7 incident response for ingestion lag and segment handoff failures
    • Version upgrade planning and operational hardening across releases
  • 05

    Druid Health Check & Assessment

    A structured review of segment sizing, query latency, and ingestion lag — delivered as a written report your team can act on.

    • Segment size and count audit against the 300–700MB target range
    • Query latency and broker cache hit-rate review
    • Ingestion lag and task failure pattern analysis
    • Written report with prioritized remediation ranked by production risk
  • 15 MIN SLA

    24/7 Apache Druid Support

    Named senior engineers on your account — 15-minute emergency response, no ticket routing, no junior triage.

    • 15-minute emergency response SLA
    • Named engineer, zero cold-start
    • Proactive CVE & health monitoring
    • Quarterly deployment reviews
    Compare the four Apache Druid support tiers

Want AceMQ to take this off your team's plate? Tell us about your Apache Druid estate.

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24/7 Support

Apache Druid Support When It Matters Most

AceMQ Apache Druid support gives you named senior engineers and a 15-minute first response when ingestion stops or queries fail, 24/7. Lower severities get 1-hour, 4-hour and next-day responses. The same response times apply to open source Druid and Imply deployments.

  1. 15 minfirst responseEmergencyProduction down, messages not flowing, queue manager failure
  2. 1 hourfirst responseCriticalSevere degradation, high error rates, approaching capacity
  3. 4 hoursfirst responseHighPerformance issues, configuration problems, non-critical failures
  4. Next Dayfirst responseStandardQuestions, guidance, best practices, non-urgent improvements

P1 escalation path

A replay of one P1, from the first page to the written root-cause analysis

SLA 15:00
T+Elapsed15:00
Engineer on your bridge

15-minute P1 response, 24/7.
A response time, not a resolution time.

  1. T+00:00

    P1 opened, on-call engineer paged

    Phone, email or Slack reaches the on-call senior engineer directly, whether the incident is in RabbitMQ, Kafka, Redis, PostgreSQL or Kubernetes. No web form, no tier-1 queue.

    Paged
  2. T+15:00

    Senior engineer on your bridge

    A senior engineer who already knows your environment joins a live bridge, so nobody has to re-explain your topology.

    Live
  3. T+30:00

    Specialists across the stack join

    When an incident crosses components, the engineers who know each one join. For RabbitMQ, the path runs to the core team.

    If needed
  4. After

    Written root-cause analysis

    Root cause, the fix applied and the prevention steps, delivered after every P1.

    Every P1

How Our Support Actually Works

Beyond SLAs — the model behind senior-only, zero-cold-start expert access.

  • Named Engineers on Your Account

    Every ticket is handled by a senior SME assigned to your account — not a pool of anonymous agents. Zero cold-start. No re-explaining your environment.

  • Live Escalation on Any Ticket

    Any ticket can be escalated to a live session with your named engineer via calendar booking. No gatekeeping, no approval required — direct access, always.

  • Proactive Risk Mitigation

    Quarterly health checks on your deployment plus shared intelligence from 50+ support customers — we surface risks before they reach production.

  • Critical Bug & CVE Intelligence

    Proactive alerts on critical bugs and CVEs affecting your exact version, with version compliance monitoring so you're never caught off guard.

  • Commercial EOL Versions

    Commercial support for end-of-life Apache Druid versions, with security fixes backported through OSSeva, so the upgrade happens on your schedule rather than the community's.

Compare Apache Druid support plans

How It Works

What actually happens next

An AceMQ Druid engagement runs in four stages: a cluster and segment review of 1 to 2 weeks, written findings within a week, compaction and tiering changes scheduled behind current load with your engineers, then a handover with runbooks. Each stage ends in writing.

1–2 weeks

Cluster and segment review

We look at segment size and granularity against query patterns, the compaction backlog, tiering and load rules across historicals, supervisor health, and task slot allocation on the middleManagers.

Within a week

Written findings and plan

Whether the latency is a segment layout problem, an ingestion problem or a query problem, and what to change first. Sized for your own engineering leadership to sign off.

Scoped per engagement

Implementation alongside your team

Compaction and re-ingestion scheduled behind current load, tiering rules changed incrementally, so queries keep serving throughout.

Ongoing

Handover and optional cover

Runbooks for stalled supervisors, segment rebalancing and node replacement, plus 24/7 support with a 15-minute emergency SLA if you want it.

  • Written findings before any change
  • Compaction and tiering changes scheduled behind current load
  • Your engineers in the room
  • You keep the runbooks
  • Ad hoc engagements or an annual partnership

A senior engineer, not an SDR. No sales sequence attached.

Customer Success

Real Apache Druid Results

Apache Druid work from AceMQ, from streaming ingestion lag remediation and query performance support to compaction design and a tiered architecture assessment. Each card links to the full write-up: the cluster, what AceMQ assessed or changed, and the result.

1 / 4 case studies

All use cases

Solutions

Every way AceMQ works with Apache Druid.

AceMQ covers Apache Druid end to end: segment and ingestion consulting, 24/7 support and incident management, proactive monitoring, managed clusters on your infrastructure or on AceMQ's, support for clusters on older releases, and a fixed-price health check.

Projects

Build, fix or move Apache Druid

Fixed-scope work led by a senior engineer: architecture and new builds, a health check of what you run today, or a migration with a reversible cutover.

Support and managed services

Keep Apache Druid running

Four tiers of ongoing cover once you are live. Each tier hands more of the day-to-day work to AceMQ, from a 15-minute emergency SLA to AceMQ hosting and running Apache Druid for you.

Compare the four Apache Druid support tiers

Side by side

Self-managed Druid, Imply or independent support: who covers what?

Apache Druid has no published support window for older releases, so support comes from the community, from Imply for its own software, or from independent engineers for self-managed clusters. AceMQ covers self-managed Druid as you run it, and each row below answers one question about the choice.

Self-managed Apache Druid, Imply and AceMQ compared on the software, who supports it, supported versions, where incidents come from, what a move involves and fit
QuestionSelf-managed Apache DruidImply (Enterprise or Polaris)AceMQ
What is the software?Open source Apache Druid, run by you on virtual machines or Kubernetes.Imply Enterprise is a commercial Druid distribution you deploy. Imply Polaris is a cloud database service built on Druid.Supports self-managed Apache Druid as it runs today, and Imply Enterprise and Polaris estates around Imply's own components.
Who supports it?The Apache Druid community, through the mailing list, Slack and GitHub, with no response time.Imply, for Imply's own software.Named senior engineers, 24/7, with a 15-minute first response on a P1.
Which versions are supported?The project publishes the latest stable release, 38.0.0 at the time of writing, and no support window for older releases.Imply's own releases, under Imply's policy.Any release you run, including ones well behind the current one. Upgrades are planned through several releases and tested on your ingestion specs.
Where do the usual incidents come from?All of them are yours: Kafka ingestion lag, segment sprawl, full Historical tiers, and metadata store or deep storage faults.Imply supports its software, but ingestion specs, segment granularity and rollup choices are still design decisions your team owns.The segment, compaction and tiering layer, the Kafka pipeline in front, and the dependencies behind Druid.
What does a move involve?Nothing if the cluster is stable and recent. Otherwise a planned upgrade across the releases in between.Migrating from open source Druid to the Imply distribution before its support applies.No migration. Support starts on the cluster as it runs today.
When does it fit?You have Druid experience in-house and can carry the pager.You want a vendor distribution or a cloud database service built on Druid.You run Druid yourself and need 24/7 cover from engineers who know the Coordinator, Broker, Historical and MiddleManager roles.

For who supports which part of Druid, and what the project does not promise, read Apache Druid support options.

Not sure which option fits? A senior Apache Druid engineer will scope it with you.

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One partner, not five

We Support Your Entire Tech Stack

Apache Druid rarely fails in isolation. AceMQ covers the full surrounding infrastructure — so one team owns the whole path instead of pointing at each other.

Messaging & Streaming

Databases & Caching

Search & Analytics

Lakehouse & Compute

Observability & Monitoring

Data Integration

Cloud & Containers

API Management

VMware Tanzu

See all 51 technologies we supportShow fewer

Guides, articles and comparisons

Go deeper on Apache Druid.

Guides from AceMQ engineers on who supports Apache Druid and what the project does and does not cover, plus the AceMQ services for the Kafka ingestion and analytics tools around it.

Related services

Ready to talk Apache Druid? Get a quote or send us a message.

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FAQs

Apache Druid Questions Answered

Eight answers on Apache Druid from AceMQ: supported versions, who answers when ingestion stops, how an engagement starts, working with your team, Kafka lag, slow queries, Imply and choosing between Druid, ClickHouse and Elasticsearch.

Still have questions about Apache Druid? Email an Expert

Which Apache Druid versions are supported?

The Apache Druid project publishes the latest stable release, 38.0.0 at the time of writing, and no support window for older releases, so a cluster that has fallen behind is on its own. AceMQ supports self-managed Druid on any release, plans upgrades through several versions, and tests them against your ingestion specs and queries first.

Who answers when Druid ingestion stops, and how fast?

A named AceMQ senior engineer answers within 15 minutes, 24/7, when ingestion has stopped, segments are unavailable or queries fail cluster-wide. Lower severities get a first response within 1 hour, 4 hours or the next business day. The engineer who takes the call stays on the case, and you get a written root-cause analysis after every P1.

How does an Apache Druid engagement with AceMQ start?

It starts with a free consultation with a senior engineer, booked in our reply within 1 hour. A cluster and segment review of 1 to 2 weeks follows, covering segment size and granularity, the compaction backlog, tiering and load rules, supervisor health and task slots. Written findings and a plan arrive within a week, before anything changes.

Can an AceMQ engineer work alongside our in-house team?

Yes. A named senior engineer works with your engineers rather than around them, changing ingestion specs, compaction settings and load rules together. Compaction and re-ingestion are scheduled behind current load, tiering rules change incrementally so queries keep serving, and you keep the runbooks for stalled supervisors and node replacement.

Our Druid Kafka ingestion keeps falling behind. Where does AceMQ start?

With the supervisor status and per-partition lag. Tasks that die and restart in a loop keep the supervisor reporting as running while offsets barely move, and task slot exhaustion on the MiddleManagers causes the same stale dashboards. AceMQ fixes the failing tasks first, then sizes task count and duration against partition count so a traffic increase does not repeat it.

Why has Druid query performance degraded slowly over months?

Almost always segment sprawl with compaction not running. A query fans out to every segment in its time range, so cost grows with segment count, and streaming ingestion creates many small segments by design. AceMQ checks the Coordinator's auto-compaction status, gives compaction its own task capacity and compacts the intervals that built up while it was off.

Does AceMQ support Imply as well as open source Druid?

Yes. AceMQ supports self-managed Apache Druid, Imply Enterprise and Imply Polaris, because the segment model, ingestion mechanics and query fan-out are the same. Where a fault sits inside Imply's own components, we say so and help you work it through Imply's support, rather than pretending to fix it.

Is Druid the right engine, or should we use ClickHouse or Elasticsearch?

Druid suits real-time streaming ingestion with rollup and predictable dashboard queries at high concurrency. ClickHouse gives more freedom for ad hoc SQL, and Elasticsearch fits full-text search better than large-scale aggregation. AceMQ benchmarks the candidates against your actual queries before recommending a move, in either direction.

Can we work with AceMQ on Apache Druid without a long contract?

Yes. AceMQ works on Apache Druid in two ways: ad hoc engagements for a defined piece of work, such as a health check, an upgrade or an incident, or an annual partner engagement that covers 24/7 support, proactive reviews and named engineers. Many teams start ad hoc and move to an annual partnership once the first engagement is done.

How much does AceMQ Apache Druid support or consulting cost?

Every AceMQ proposal is tailored to your requirements: your Apache Druid environment, the SLA you need, the hours of cover and the scope of work. Most contracts run $24,000–72,000 a year, depending on the SLA, the scope and how Apache Druid is deployed, with aggressive discounts when several technologies share one contract. Request a quote and AceMQ replies within 1 hour.

Let's talk

Ready to Stabilize Your Druid Environment?

Whether you need emergency support, a healthcheck, a migration off Elasticsearch or a warehouse, or ongoing managed support — AceMQ staffs every engagement with a named senior Druid engineer. Quote requests answered within 1 hour.

A senior Druid engineer, not a sales queueAbout your cluster, not a pitch deckQuote requests answered within 1 hour

Production incident right now?Email an Apache Druid Architect

Get in Touch

Talk to an Apache Druid Expert

Send us a message and we'll follow up within 1 hour — or book a free 30-min consultation directly.

305-204-2607
info@acemq.com
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Miami, FL 33130

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