Apache Cassandra Consulting & Support

Apache Cassandra Consulting & Support for Enterprises

AceMQ engineers model wide-column data around your queries, not the other way around, and run the multi-datacenter clusters that keep writing through a regional outage. Every engagement is staffed by a named senior engineer with real production Cassandra experience.

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

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

Without remodelling every table or moving off CassandraFor production incident cover, see AceMQ Apache Cassandra 24/7 support.

Customers

  • Microsoft
  • Henry Schein
  • Enbridge
  • Gojek

Partners

  • Broadcom
  • Redis
  • VMware Tanzu
  • OSSeva

The Problem

Why teams call us about Apache Cassandra

Eight Cassandra problems teams bring to AceMQ, from partitions that grew to hundreds of megabytes and tombstones that push reads past the failure threshold to repairs that miss gc_grace_seconds and GC pauses that look like node failures. If one describes your week, that is where the review starts.

  1. 01

    A partition has grown into the hundreds of megabytes and reads against it now time out

  2. 02

    Tombstones from a delete-heavy table push queries past the tombstone failure threshold

  3. 03

    Repairs have not completed inside gc_grace_seconds and deleted data has started coming back

  4. 04

    Compaction never catches up, so SSTable counts climb and read latency climbs with them

  5. 05

    One node in the ring runs hotter than the rest and nobody can explain the token ownership

  6. 06

    A LOCAL_QUORUM write succeeds while the remote datacenter quietly falls further behind

  7. 07

    Long GC pauses on the JVM are reported to the application as node failures

  8. 08

    The DataStax Enterprise renewal is due and nobody has costed the open-source path

A good fit if you run Apache Cassandra in production, on one datacenter or several, and want senior engineers who stay on a problem until the root cause is written down.

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 Cassandra.

Running Apache Cassandra 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 your reads when a Cassandra replica is down?

A replica that is down for longer than max_hint_window misses writes that no hint will replay. When it returns, a read at consistency ONE can reach it and return stale rows, or bring back deleted data once the tombstone is purged. Only a repair that finishes inside gc_grace_seconds closes the gap.

Replica outage with a missed repair

Application, driver, replicas A, B and C in one datacenter

Illustrative

  1. The driver is token-aware and reads from the replicas that own the partition. All three replicas hold the same data, and hinted handoff covers short gaps.

  2. Replica A is down past max_hint_window. Replica B missed writes and was never repaired, yet reads at ONE are served by it, so the application sees stale rows and, later, deleted data returning.

  3. Repair now completes inside gc_grace_seconds, so replica C holds current data. Reads and writes use LOCAL_QUORUM, which needs two replicas to agree, and a stale replica is outvoted.

Stale reads and resurrected deletes are among the reasons teams call AceMQ about Cassandra. The fix is operational discipline plus design: a repair schedule that completes every table inside gc_grace_seconds, usually subrange repair driven by a scheduler such as Reaper, LOCAL_QUORUM for reads and writes that must agree, a replication factor of three per datacenter, a snitch and NetworkTopologyStrategy datacenter names that match, and an outage runbook that decides whether hints are enough or a repair is required. A data model change often removes the tombstones in the first place.

Our Services

Apache Cassandra Consulting & Services

AceMQ runs five Cassandra service lines: data modeling and architecture, performance and compaction tuning, migration from relational databases, managed operations with 24/7 support, and a structured health check. A named senior engineer leads each one, and any of them can roll into 24/7 support with a 15-minute emergency SLA.

  • 01

    Cassandra Data Modeling & Architecture

    Cassandra data modeling starts with the query, not the entity — get the partition key wrong and no amount of tuning fixes the resulting hotspot. We design tables around your access patterns from day one.

    • Query-first data modeling with partition key selection to avoid hotspots
    • Wide-column table design for time-series and high-write-throughput workloads
    • Multi-datacenter replication architecture with NetworkTopologyStrategy for geo-distribution
    • Consistency level selection (QUORUM, LOCAL_QUORUM) matched to SLA requirements
  • 02

    Performance Tuning & Compaction Strategy

    The wrong compaction strategy for your workload shows up as read latency creep or disk pressure months later. We match STCS, LCS, or TWCS to how your data actually gets written and read.

    • Compaction strategy selection — STCS, LCS, or TWCS — matched to workload shape
    • Tombstone and garbage collection grace period tuning to prevent read-path slowdowns
    • JVM heap and G1GC tuning for predictable p99 latency
    • Read/write path profiling with nodetool and tracing to isolate bottlenecks
  • 03

    Migration from Relational Databases

    Cassandra migrations usually start the same way: write throughput outgrew what a relational cluster could scale to. We denormalize around your queries and cut over with zero data loss.

    • Denormalization and query-table redesign migrating off Oracle, SQL Server, or PostgreSQL
    • Dual-write cutover strategy for zero-downtime production migrations
    • Cross-version migration planning across Cassandra 2.x, 3.x, and 4.x operational changes
    • Evaluation against MongoDB's document model when access patterns favor it instead
  • 04

    Managed Operations & 24/7 Support

    Repairs that don't run on schedule turn into entropy and, eventually, resurrected deleted data. We keep the maintenance cadence that keeps a Cassandra cluster healthy over years, not weeks.

    • Capacity planning and node sizing ahead of ingest growth
    • Repair scheduling — incremental and full — to prevent entropy and data resurrection
    • 24/7 incident response for node flapping, hinted handoff backlog, and GC pauses
    • Rolling upgrade execution across major versions with zero downtime
  • 05

    Cassandra Health Check & Assessment

    A structured review of partition sizing, compaction backlog, and repair history — delivered as a written report your team can act on.

    • Partition size and hotspot audit across keyspaces
    • Compaction backlog and SSTable count review
    • Repair history and consistency risk assessment
    • Written report with prioritized remediation ranked by production risk
  • 15 MIN SLA

    24/7 Apache Cassandra 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 Cassandra support tiers

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

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24/7 Support

Apache Cassandra Support When It Matters Most

AceMQ Cassandra support gives you a named senior engineer and a 15-minute first response when production is down, 24/7, on open source Cassandra, DataStax Enterprise or Kubernetes. Lower severities get 1-hour, 4-hour and next-day responses, and every P1 ends with a written root-cause analysis.

  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 Cassandra versions, with security fixes backported through OSSeva, so the upgrade happens on your schedule rather than the community's.

Compare Apache Cassandra support plans

How It Works

What actually happens next

An AceMQ Cassandra engagement runs in four stages: a ring and data model review of 1 to 2 weeks, written findings within a week, compaction, repair and node changes staged one node at a time so the ring keeps serving at your consistency level, then a handover with runbooks for node replacement, repair cadence and datacenter failover.

1–2 weeks

Ring and data model review

We look at partition size distribution, tombstone counts, compaction strategy against the write pattern, repair history, token ownership across the ring, and the queries the tables were actually built to serve.

Within a week

Written findings and plan

Which partitions and which access patterns are causing the timeouts, which are only correlated with them, and what to change first. Sized for your own engineering leadership to sign off.

Scoped per engagement

Implementation alongside your team

Compaction strategy changes, repair scheduling and node replacements staged one at a time, so the ring keeps serving at your required consistency level throughout.

Ongoing

Handover and optional cover

Runbooks for node replacement, repair cadence and datacenter failover, plus 24/7 support with a 15-minute emergency SLA if you want it.

  • Written findings before any change
  • Compaction, repair and node changes staged one node at a time
  • 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 Cassandra Results

AceMQ case studies where Apache Cassandra was part of the estate, from tombstone-driven read timeouts to repair and compaction support and data model design. Each one links to the full write-up: the environment, what AceMQ assessed or changed, and the result.

1 / 4 case studies

  • Support

    Cassandra Repair and Compaction Support

    Global Payments Processor

    Ongoing support for anti-entropy repair that never completed within gc_grace_seconds, leaving the cluster exposed to deleted data resurrecting.

    Apache CassandraReaperPrometheusKubernetes
    Read case study : Cassandra Repair and Compaction Support
  • Consulting

    Cassandra Data Model and Partition Design Consulting

    Digital Identity Services Provider

    Redesigning partition keys and clustering order to eliminate unbounded partitions and remove secondary index queries that were hitting every node.

    Apache CassandraKubernetesKafkaPrometheus
    Read case study : Cassandra Data Model and Partition Design Consulting
  • Assessment

    Cassandra Cluster Health and Capacity Assessment

    Public Sector Agency

    Assessment covering topology, replication and consistency configuration, JVM and garbage collection behavior, compaction health, and growth headroom.

    Apache CassandraLinuxPrometheusKubernetes
    Read case study : Cassandra Cluster Health and Capacity Assessment
All use cases

Solutions

Every way AceMQ works with Apache Cassandra.

AceMQ covers Apache Cassandra end to end: consulting and upgrades, 24/7 support and incident management, proactive monitoring, managed Cassandra on your infrastructure or on AceMQ's, cover for unmaintained 3.x clusters, and a fixed-price health check.

Projects

Build, fix or move Apache Cassandra

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 Cassandra 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 Cassandra for you.

Compare the four Apache Cassandra support tiers

Side by side

Self-managed Cassandra or a managed service: what do you still own?

Managed Cassandra services such as Amazon Keyspaces, Azure Managed Instance for Apache Cassandra or DataStax Astra remove part of the operational surface, and Keyspaces hides compaction and repair entirely. Self-managed Cassandra leaves all of it with your team. Either way, partition design, consistency levels and delete patterns stay with you.

Managed Cassandra services compared with self-managed Cassandra on who runs the nodes, tuning, end of life, incidents, cost shape and exit
QuestionManaged service (Keyspaces, Azure Managed Instance, Astra)Self-managed (VMs, Kubernetes, bare metal)
Who runs the nodes, repair and upgrades?The provider, to a varying degree. Keyspaces hides repair and compaction, while Azure Managed Instance exposes the cluster but automates patching.Your team, or a specialist on call, including repair schedules and rolling upgrades.
Which settings and versions can you use?Only what the service supports. Keyspaces is Cassandra-compatible rather than Cassandra, and some CQL features and settings are missing.Any setting, compaction strategy and Apache Cassandra version, including custom builds.
What happens at end of life?The provider retires versions on its own calendar and moves you.Apache Cassandra maintains 5.0, 4.1 and 4.0, and 3.11 is unmaintained. You choose the upgrade date.
Who answers a database incident?The provider's support runs the service. Partition size, tombstones, consistency level and driver policy stay with your team.Your team, or AceMQ: a named senior engineer, 24/7, a 15-minute emergency response and a written root-cause analysis for every P1.
What does it cost?Provisioned or on-demand capacity on the cloud invoice. A wide partition or a hot key still changes what you pay.Your own infrastructure, plus a support contract priced on the cover you need.
How do you leave?Export or stream the data out. Provider-specific features and limits shape the move.Nothing to exit. Runbooks and topology documentation are yours.

For what the Cassandra project, vendors and independent support each cover, read Apache Cassandra support options compared.

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

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One partner, not five

We Support Your Entire Tech Stack

Apache Cassandra 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 Cassandra.

Guides from AceMQ engineers on Cassandra support options and who covers unmaintained 3.x clusters, plus the AceMQ services for the databases and streaming systems that usually run next to Cassandra. Each link goes to the full article or service page.

Related services

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

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FAQs

Apache Cassandra Questions Answered

Eight answers on Apache Cassandra from AceMQ: who answers when a cluster fails, supported versions, what consulting includes, tombstone timeouts, repair, upgrades off 3.11, compaction strategy, and fixing performance without more nodes.

Still have questions about Apache Cassandra? Email an Expert

Who answers when a Cassandra cluster fails in production, and how fast?

A named AceMQ senior engineer answers within 15 minutes, 24/7, when several nodes are down, reads or writes are failing cluster-wide or a ring will not converge, on open source Cassandra, DataStax Enterprise or Kubernetes. Lower severities get a first response within 1 hour, 4 hours or the next business day, with a written root-cause analysis after every P1.

Which Cassandra versions are still supported?

The Apache Cassandra project maintains 5.0, 4.1 and 4.0, and 3.11 is no longer maintained. The project has no end-of-life dates, only maintenance until a later release. AceMQ supports Cassandra 3.11 through 5.0 24/7, and plans the move off 3.11 in parallel, because mixed versions cannot stream to each other.

What does Apache Cassandra consulting from AceMQ include?

Our Cassandra consulting covers query-first data modeling, partition key design, multi-datacenter replication, compaction strategy, JVM tuning, repair scheduling and migration planning. A named senior engineer leads each engagement, delivers written findings before changing anything, and works alongside your team.

Our reads time out on a table we delete from often. What is happening?

Tombstones. Cassandra writes a marker on every delete and every expired TTL, and each read of that partition scans the markers until they age past gc_grace_seconds and compaction removes them. A query that scans past tombstone_failure_threshold is aborted. We give relief with targeted compaction, then fix repair, then change the data model, often to time-bucketed partitions with TWCS.

How often does repair need to run, and why does it keep failing?

Every table needs a repair to complete inside gc_grace_seconds, ten days by default, or deleted data can return. Repairs fail from very wide partitions that exceed stream timeouts, too little compaction throughput, full repairs where subrange would fit, and overlapping sessions. We move teams to a scheduled subrange repair with margin, so it finishes before the window, not on its last day.

Can you help us upgrade from Cassandra 3.11 to 4.x or 5.0?

Yes. It is a rolling upgrade, and nodes on different major versions cannot stream to each other, so no bootstrap, decommission or repair can run until the whole ring is upgraded. We rehearse on a cloned cluster, check driver compatibility, upgrade SSTables node by node and keep a tested rollback point.

How do you choose a compaction strategy?

By the write and read pattern, not by default. Size-tiered suits write-heavy tables with few updates, leveled suits read-heavy tables that need steady latency, and time-window suits time-series data with TTL expiry. A mismatch shows up months later as climbing SSTable counts and read latency, so we measure pending compactions before we change it.

Can you fix Cassandra performance without a bigger cluster?

Usually. Most performance problems are data model problems found at scale: a partition key that lets one partition grow to gigabytes, queue-like deletes, secondary indexes on high-cardinality columns, or a compaction strategy chosen for another workload. Others are heap and GC settings or repair schedules that collide with peak load. We tell you plainly when the answer is more nodes.

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

Yes. AceMQ works on Apache Cassandra 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 Cassandra support or consulting cost?

Every AceMQ proposal is tailored to your requirements: your Apache Cassandra 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 Cassandra 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 Cassandra Environment?

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

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

Production incident right now?Email an Apache Cassandra Architect

Get in Touch

Talk to an Apache Cassandra Expert

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

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info@acemq.com
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Miami, FL 33130

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