Managed Cassandra vs Self-Hosted in 2026
Over the past several years, the managed Cassandra market has grown steadily as AWS launched Keyspaces, Azure introduced both the Cosmos DB CQL API and later a Managed Instance, Instaclustr (now part of NetApp) built a managed Cassandra business across multiple clouds, DataStax launched Astra DB, and Aiven added managed Cassandra to its portfolio.
Every one of these providers sold the same message: that Apache Cassandra is too operationally complex for most teams to run themselves, and that handing over the operational responsibility to a managed service provider is the sensible choice. For a long time that argument held up reasonably well, because the tooling ecosystem around self-hosted Cassandra was genuinely lacking. Monitoring required stitching together multiple disparate tools, repair scheduling was manual and error-prone, backups demanded custom scripting, and without a dedicated team of Cassandra specialists it was difficult to justify doing it all yourself.
That situation has changed considerably in 2026, and this article looks at the managed options available today, what they actually give you, what they cost, and why the case for self-hosting Apache Cassandra with proper tooling is now stronger than it has ever been.
The Managed Cassandra Landscape
An important distinction that often gets lost in vendor marketing is that not all managed Cassandra services actually run Apache Cassandra. Some of them are proprietary databases that expose a CQL-compatible interface, and the practical differences between those two categories are substantial.
AWS Amazon Keyspaces
Keyspaces tends to be the first option that enterprises on AWS evaluate, but it is important to understand that Keyspaces is not Apache Cassandra. It is a proprietary AWS service, widely understood to be built on top of DynamoDB’s storage backend, that provides a CQL-compatible API layer.
The limitations that follow from this architecture are significant:
- No secondary indexes, materialized views, user-defined functions or aggregates, or triggers
- No TRUNCATE command, and no server-side aggregate functions such as COUNT, SUM, AVG, MIN, or MAX
- Severely restricted consistency levels: only LOCAL_ONE, ONE, and LOCAL_QUORUM are available for reads, and only LOCAL_QUORUM for writes, with no support for QUORUM, ALL, TWO, THREE, EACH_QUORUM, or ANY
- No SSTable access whatsoever, meaning you cannot export or import SSTables, use sstableloader, or perform bulk loading with Cassandra-native tools
- No nodetool, since the service is serverless and there are no nodes to manage
- No compaction configuration, with compression, caching, bloom filter, and gc_grace settings all ignored
- Authentication limited to AWS IAM, with no support for Cassandra native authentication
For applications that were built against Apache Cassandra, migrating to Keyspaces involves discovering which features are no longer available and working around them. Migrating away from Keyspaces requires a full data export and re-import because the underlying data is stored in a proprietary backend rather than in SSTables. The per-operation pricing model also becomes increasingly expensive at higher throughput levels, as discussed in the cost section below.
Azure Cosmos DB Cassandra API
Like Keyspaces, the Cosmos DB Cassandra API is a proprietary database with a CQL interface rather than Apache Cassandra itself, running on Cosmos DB’s multi-model storage engine with CQL layered on top.
The gaps relative to real Cassandra are extensive. It supports only CQL v3.11 with no Cassandra 4.x or 5.x features, does not support logged batches, and lightweight transactions do not work with multi-region writes. Row sizes are capped at 2 MB and partition sizes at 20 GB. The replication factor is fixed at 4 with no ability to modify it. There is no CREATE KEYSPACE replication control, no COPY command, and no tracing. Rate limiting is enforced through Request Units, and exceeding your RU budget results in 429 errors. Azure’s own documentation acknowledges that lift-and-shift migrations from Cassandra can be challenging due to differences in behaviour and configuration.
The vendor lock-in with Cosmos DB is particularly deep because your data resides in a proprietary storage engine, your capacity planning is done in Request Units (a concept specific to Cosmos DB with no equivalent elsewhere), and while the consistency model is mapped to Cassandra consistency levels, the actual behaviour is not identical.
Azure Managed Instance for Apache Cassandra
Unlike Keyspaces and Cosmos DB, Azure Managed Instance actually runs real open-source Apache Cassandra (up to version 5.0), which means your data is stored in genuine SSTables. However, there are still meaningful restrictions on what you can do with it.
Nodetool access is limited to read-only commands, with management commands available only in Public Preview with no SLA guarantees and an explicit warning from Azure that they could destabilise the cluster. The service supports a maximum of 100 nodes per data centre through the portal, only Premium Disk (P30) storage is available, and the built-in monitoring retains only 10 minutes or 10 GB of data (whichever threshold is reached first). It is also an Azure-only service with no multi-cloud option.
While your data is portable because it consists of real SSTables, all of your operational tooling is Azure-specific, so moving to another provider means rebuilding your entire monitoring, alerting, backup, and management infrastructure from scratch.
Instaclustr (NetApp)
Instaclustr runs unmodified open-source Cassandra on AWS, Azure, or GCP with support up to Cassandra 5.0, making it one of the most portable managed options since your data lives in standard SSTables.
The trade-off is that you give up operational control in exchange for convenience: there is no full root or SSH access to nodes, configuration changes go through Instaclustr’s platform rather than directly through cassandra.yaml, version upgrades happen on their timeline rather than yours, and scaling operations are managed by Instaclustr rather than by your team. The data is portable, but the operational tooling is not, and at larger cluster sizes (dozens to hundreds of nodes) the management markup over the raw infrastructure cost becomes a substantial recurring expense.
DataStax Astra DB (IBM)
Astra DB is a serverless Cassandra-as-a-service built on DataStax Enterprise (DSE), which is itself a proprietary extension of Apache Cassandra rather than the community open-source version. In February 2025, IBM acquired DataStax with the stated intention of integrating it into the watsonx AI platform.
The service has a number of limitations that reflect both its serverless architecture and DSE’s divergence from community Cassandra: there is no cassandra.yaml configuration or tuning of core settings, no CREATE KEYSPACE or DROP KEYSPACE via CQL, a maximum of 50 columns per table, a maximum of 10 indexes per table, and a 5 MB limit on single column values. The consistency model is restricted, with no support for ONE, ANY, or LOCAL_ONE for writes, and the underlying database is DSE rather than pure open-source Cassandra.
IBM’s acquisition raises legitimate questions about the long-term direction of the product, as their stated plan is to fold DataStax into the watsonx AI platform, and IBM’s track record with acquisitions generally points towards deeper integration into their own ecosystem rather than increased vendor neutrality.
Aiven for Apache Cassandra
Aiven provides perhaps the most instructive example of managed service risk: they discontinued their managed Cassandra service entirely. As of December 2025, no new services could be created, and on 7 January 2026 all existing services were powered off and permanently deleted, forcing customers to emergency-migrate their data before a hard deadline after which it became permanently inaccessible.
This illustrates a fundamental risk of relying on any managed service for a core database: the provider can simply decide to stop offering the product, and your options at that point are limited to whatever migration window they choose to give you.
What It Actually Costs
Managed Cassandra providers use different pricing models, which makes direct comparison difficult. Some charge per operation, some use Request Units, and some charge per node with a management markup on top. When you normalise the numbers against a common workload, however, the differences become very clear.
The comparison below is based on a mid-sized production workload running a 6-node cluster on AWS with i3.2xlarge instances (8 vCPUs, 61 GB RAM, 1.9 TB NVMe, which is a common instance type for Cassandra), handling approximately 50,000 reads and 25,000 writes per second with an average item size of 1 KB.
Self-Hosted Baseline
Running 6x i3.2xlarge instances on AWS with on-demand pricing comes to roughly $2,736/month ($0.624/hr × 6 × 730 hours), and this drops significantly with reserved instances: 1-year reservations reduce the cost by approximately 40%, and 3-year reservations by approximately 60%. The total cost is simply the VMs, storage (which is included with i3 instances), and network transfer.
AWS Keyspaces
With on-demand capacity mode at 50K reads/sec and 25K writes/sec, Keyspaces costs approximately $32,500/month, which is about 12× the self-hosted cost for equivalent throughput. The per-operation pricing model appears inexpensive at low volumes but becomes punishing at production scale, and even switching to provisioned capacity with reserved pricing still results in a cost multiple of the self-hosted baseline.
DataStax Astra DB
Astra’s serverless pricing based on read/write units produces estimated costs of approximately $64,000/month at comparable throughput levels, which is roughly 23× the self-hosted cost. The service is optimised for convenience and low-volume workloads; at production throughput, the cost structure does not scale well.
Instaclustr (NetApp)
Instaclustr applies a management markup on top of the underlying cloud infrastructure, and based on their published pricing for comparable node configurations, a 6-node cluster costs approximately $7,200–9,600/month, which represents roughly 2.6–3.5× the raw infrastructure cost. This is the most reasonable markup among the managed providers, but over a three-year period the additional cost amounts to $160,000–250,000, which is more than enough to fund proper operational tooling and the people to use it.
Azure Managed Instance for Apache Cassandra
Azure Managed Instance runs real Cassandra on Standard_DS14_v2 VMs, and for a comparable 6-node cluster the cost is approximately $3,900/month, which is about 1.4× the self-hosted cost on Azure. While the markup is relatively modest, the trade-offs include being locked into Azure, having only P30 disk options, and monitoring that retains just 10 minutes of historical data.
The Cost Picture
| Provider | Self-Hosted (AWS) | AWS Keyspaces | Instaclustr | Azure MI | DataStax Astra |
|---|---|---|---|---|---|
| Monthly Cost (6-node equiv.) | ~$2,736 | ~$32,500 | ~$7,200–9,600 | ~$3,900 | ~$64,000 |
| Markup vs Self-Hosted | 1× (baseline) | ~12× | ~2.6–3.5× | ~1.4× | ~23× |
| 3-Year Extra Cost | $0 | ~$1.07M | ~$160–250K | ~$42K | ~$2.2M |
| Pricing Model | Infrastructure only | Per-operation | VM + management fee | VM + markup | Per-operation (RUs) |
Estimates based on 6× i3.2xlarge-equivalent nodes, 50K reads/sec + 25K writes/sec, 1 KB average item size, on-demand pricing, us-east-1. Actual costs vary by workload, region, and pricing tier. Self-hosted cost excludes reserved instance discounts, which would reduce it further.
The per-operation services like Keyspaces and Astra appear attractive at low throughput, but the cost curve steepens dramatically once you reach production-level volumes. Even Instaclustr’s more moderate markup compounds to hundreds of thousands of pounds over a few years, which represents a significant amount of infrastructure and tooling budget.
The Case for Self-Hosting in 2026
Full Control
Self-hosting gives you direct access to every aspect of your Cassandra deployment. You have complete control over cassandra.yaml, allowing you to tune memtable sizes, compaction strategies (including SizeTiered, Leveled, TimeWindow, and Cassandra 5.0’s Unified Compaction), bloom filters, compression settings, gc_grace_seconds, read repair behaviour, and hinted handoff configuration. You control JVM settings including heap size and garbage collection strategy, with support for JDK 21’s Generational ZGC in Cassandra 5.0. You have full nodetool access to run repair, cleanup, compact, decommission, and rebuild operations on your own schedule. And you can run any version of Cassandra you choose, including the latest 5.0 release with Storage Attached Indexes (SAI), vector search, and the Accord distributed transaction protocol, without waiting for a managed provider to certify it.
There are no artificial feature restrictions, no column count limits, no Request Unit budgets, and no restricted consistency levels.
No Vendor Lock-In
When you self-host, your data lives in standard SSTables on disks that you control, which means you can move between cloud providers, adopt a hybrid architecture, or run on bare metal without being dependent on any proprietary API, billing model, or management platform. The experiences of Aiven customers who had to emergency-migrate when the service was discontinued, and the uncertainty surrounding DataStax following IBM’s acquisition, are concrete illustrations of why vendor independence matters for a core database.
Cost Savings at Scale
As the cost comparison above demonstrates, managed services become disproportionately expensive as throughput increases. Self-hosting on reserved instances can cost as little as one tenth of what the serverless providers charge, or one third of what the more reasonably priced managed options cost at equivalent scale. There are documented cases of organisations saving more than $500,000 per year by migrating from managed Cassandra to self-hosted open-source deployments, often achieving better performance in the process.
The cost model for self-hosting is straightforward: you pay for infrastructure (VMs, storage, and network) with no per-operation charges or management premiums, and you retain the freedom to optimise costs further through reserved instances, spot instances, or bare metal deployments.
AxonOps
AxonOps is a unified operations platform purpose-built for Apache Cassandra that addresses the operational challenges which historically drove teams towards managed services:
- Monitoring: customisable dashboards with deep Cassandra-specific metrics, logs, and alerting, focused on the operational information that Cassandra teams actually need rather than generic infrastructure metrics
- Intelligent Repair: health-aware repair scheduling that dynamically throttles repair intensity based on query latencies, blocked threads, and node performance, preventing repairs from impacting cluster performance during periods of high demand
- Backup and Recovery: configurable backup with Point-in-Time Restore (PITR), supporting local storage, SSH/SFTP, Amazon S3, Google Cloud Storage, and Azure Blob as storage targets
- Nodetool Scheduling: the ability to schedule and automate nodetool operations across your cluster from a central interface
- Kubernetes Support: full monitoring, alerting, backup, and repair capabilities for Cassandra deployments running on Kubernetes
- Cassandra 5.0 Support: updated alongside the latest Apache Cassandra releases
AxonOps is available as both a SaaS service and a self-hosted deployment, with per-node pricing that is independent of instance size, so there is no cost penalty for scaling up your hardware. The total cost is a fraction of the management markup charged by any of the managed Cassandra providers discussed above.
The argument that Cassandra is too operationally complex to run yourself was reasonable when the tooling ecosystem was immature, but with a purpose-built operations platform like AxonOps handling monitoring, repair, backup, and scheduling, that argument no longer holds in 2026.
The Bottom Line
| Capability | Self-Hosted + AxonOps | AWS Keyspaces | Cosmos DB CQL | Azure MI Cassandra | Instaclustr | DataStax Astra |
|---|---|---|---|---|---|---|
| Real Apache Cassandra | ✓ Always | ✗ Proprietary | ✗ Proprietary | ✓ Yes | ✓ Yes | ◐ DSE fork |
| Cassandra 5.0 Features | ✓ Full | ✗ N/A | ✗ N/A | ✓ Yes | ✓ Yes | ◐ Partial |
| cassandra.yaml Control | ✓ Full | ✗ None | ✗ None | ◐ Limited | ◐ Limited | ✗ None |
| All Consistency Levels | ✓ Full | ✗ 3 read / 1 write | ✗ Mapped | ✓ Full | ✓ Full | ◐ Restricted |
| Secondary Indexes / SAI | ✓ Full | ✗ No | ◐ Partial | ✓ Full | ✓ Full | ◐ Partial |
| Lightweight Transactions | ✓ Full | ◐ Simplified | ✗ No (multi-region) | ✓ Full | ✓ Full | ◐ Limited |
| SSTable Access | ✓ Full | ✗ No | ✗ No | ◐ Limited | ◐ Limited | ✗ No |
| Custom Compaction | ✓ Full | ✗ No | ✗ No | ◐ Limited | ◐ Limited | ✗ No |
| Multi-Cloud | ✓ Any | ✗ AWS only | ✗ Azure only | ✗ Azure only | ✓ Multi-cloud | ✓ Multi-cloud |
| Vendor Lock-In Risk | ✓ None | ✗ Very High | ✗ Very High | ◐ Medium | ◐ Low-Medium | ✗ High (IBM) |
| Cost at Scale | ✓ Infrastructure only | ✗ Per-operation | ✗ Request Units | ◐ VM + markup | ◐ VM + markup | ✗ Per-operation |
| Risk of Discontinuation | ✓ Zero (open source) | ◐ AWS decision | ◐ Azure decision | ◐ Azure decision | ◐ NetApp decision | ✗ IBM direction uncertain |
Managed Cassandra served a genuine purpose when self-hosting was operationally difficult, but in 2026, with Cassandra 5.0’s operational improvements and platforms like AxonOps providing a complete control plane for monitoring, repair, backup, and scheduling, the trade-offs involved in using a managed service no longer make sense for most organisations. Self-hosting delivers more features, more control, lower costs at scale, and complete vendor independence.
Want to see how AxonOps makes self-hosted Cassandra operations straightforward? Try the demo sandbox or book an expert consultation.