ScyllaDB · CQL · Alternator · SeastarScyllaDB, Cassandra speed without the JVM.
ScyllaDB is a distributed, wide-column NoSQL database written in C++ as a drop-in, zero-JVM replacement for Apache Cassandra and AWS DynamoDB (via Alternator). Its Seastar shard-per-core asynchronous architecture delivers 10x higher throughput and consistent sub-5ms P99 latency. JusDB provides 24/7 ScyllaDB SRE: shard balancing, live Cassandra/DynamoDB migrations, Alternator optimization, and 24/7 on-call incident response.
Expert ScyllaDB consulting for high-performance distributed databases. Cassandra migration, cluster architecture, and Alternator (DynamoDB-compatible API) deployment. 10x faster than Cassandra.
JUSDB_SCYLLA_PRODScyllaDB 6 · shard-per-core
Masterless ring · RF=3 · tablets
0.00M
0.3ms
98.0%
96.0%
Cluster Throughput
0.00M ops/s[OK] seastar: reactor balanced across 64 shards, 0 stalls
[INF] compaction: ICS tier merged, SSTables 14 → 6
[OK] repair: row-level repair complete, RF=3 consistent
[INF] tablets: migrated 3 tablets to new node, rebalanced
Representative cluster view · illustrative metrics
0+
ScyllaDB Nodes Managed
0.99%
Uptime SLA
0M+
Ops/sec at Scale
0%
Cost Savings vs Cassandra
What we do
ScyllaDB consulting
Deep expertise in ScyllaDB's shard-per-core architecture and enterprise deployment patterns.
Cluster Architecture
Design multi-datacenter ScyllaDB clusters with optimal replication and topology strategies.
Cassandra Migration
Zero-downtime migration from Apache Cassandra to ScyllaDB with full data validation.
Performance Tuning
Shard-per-core optimization, compaction strategies, and workload-specific tuning.
Alternator Setup
DynamoDB-compatible API deployment for AWS migration and multi-cloud strategies.
High Availability
Rack-aware replication, consistency tuning, and disaster recovery configuration.
24/7 Operations
Comprehensive monitoring, alerting, and expert incident response support.
Shard-per-core performance
ScyllaDB expertise
tuned to the core
ScyllaDB's C++ Seastar engine pins one shard per CPU core with no JVM and no garbage-collection pauses. We tune compaction, balance shards, and let tablets rebalance data automatically for predictable low latency.
Cluster Performance
After tuning3×
Throughput / node
70%
Fewer nodes
Shard Architecture
ScyllaDB Shard-per-Core Failure Modes
While C++ Seastar eliminates JVM garbage collection pauses, ScyllaDB introduces shard-level lockless execution dynamics where hot partitions saturate individual CPU cores. Here is how JusDB eliminates these bottlenecks.
Shard CPU Imbalance & Hot Core Saturation
Because ScyllaDB pins one execution thread per CPU core (shard-per-core), a poorly chosen partition key maps high query traffic to a single shard. One core hits 100% CPU utilization while others remain idle, causing sharp P99 latency regressions and dropped requests.
Auditing token distribution, introducing composite partition keys with synthetic salt bucketing, and monitoring per-shard reactor metrics (reactor_utilization) in ScyllaDB Monitoring.
AIO Queue Backlog & IOPS Scheduler Starvation
Aggressive background compactions or intensive full-table scans exhaust asynchronous I/O queues (libaio). If IO scheduler shares are misconfigured, foreground CQL read/write operations get queued behind bulk compaction I/O.
Calibrating scylla_io_setup benchmarks, tuning compaction_static_shares and statement_shares, and deploying NVMe SSDs with direct I/O.
Alternator Streams & DynamoDB Attribute Mismatch
When migrating DynamoDB workloads to ScyllaDB Alternator, unhandled nested JSON schema differences or unindexed secondary attributes cause full-scan filtering, overwhelming shard memory buffers and causing HTTP 500 error spikes.
Pre-validating DynamoDB schema definitions against Alternator feature matrix, deploying local secondary indexes (LSI), and testing edge-case JSON scalar types.
Node Telemetry
Production ScyllaDB Diagnostic Commands
Critical non-blocking diagnostic commands our ScyllaDB SREs execute via the REST API and nodetool to isolate core imbalances and I/O scheduler starvation.
Queries ScyllaDB's internal Seastar reactor metrics to identify hot shards operating at 100% CPU while companion cores sit idle.
# Query per-shard CPU reactor utilization and queued background tasks curl -s http://127.0.0.1:10000/reactor/utilization | jq . # Alert if any single shard utilization > 90% while cluster average < 50%
Inspects thread queues and cross-shard communication buffers to detect dropped mutations or cross-node coordinator timeouts under heavy burst traffic.
# Check for dropped CQL requests, mutations, and internal messaging queues nodetool tpstats | grep -E 'cql_server|messaging_service|Dropped' # Ensure dropped request count remains exactly 0 across all operational stages
Real cases
Workloads we've transformed
30 nodes
0.9ms
Same workload on a 30-node Cassandra cluster
The fix
Migrated to 9 ScyllaDB nodes (shard-per-core) — p99 18ms → 0.9ms, ~70% lower spend
14ms
0.8ms
One core pinned by a hot partition (shard imbalance)
The fix
Re-bucketed partition key; tablets rebalanced load across all shards
9,200ms
1.2ms
Multi-GB partition causing reactor stalls
The fix
Split with time-bucketing; tablets distributed scan across nodes
0.00%
Ring Uptime
0%
Repair Synced
0.5ms
Read p99
Shard-per-core (Seastar) · tablets rebalance data automatically as nodes join or leave.
High availability
Always on. Masterless ring.
Every node in a ScyllaDB cluster is a peer — there is no master to fail. Data is replicated across racks and datacenters with tunable consistency, and tablets rebalance automatically as nodes join or leave, for real 99.99% uptime, not a theoretical SLA.
Incident response
A hot-shard P1, handled in under 15 minutes.
When a hot partition pins one core and p99 latency climbs, a named ScyllaDB engineer responds — not a ticket queue. Re-bucketing the partition key and letting tablets rebalance restores balance online, with a blameless postmortem after.
One shard hot — p99 read latency climbing on DC-east
Named ScyllaDB engineer in under 15 min, not a ticket queue
Hot partition pinned to one core — shard imbalance
Re-bucketed partition key + enabled tablets to rebalance
Shards balanced, p99 9ms → 0.7ms — total 14 min
Pre-Migration Assessment
Cassandra / DynamoDB → ScyllaDB
Near-zero-downtime cutover via dual-write (CQL + Alternator/DynamoDB API)
Migration
Move to ScyllaDB without the downtime
Cassandra or DynamoDB → ScyllaDB. We analyze schema and keyspaces (CQL), bulk-load with the ScyllaDB Migrator or sstableloader, replicate via dual-write to near-zero lag, and cut over with minimal disruption.
Technology stack
Technologies We Work With
Complete ScyllaDB ecosystem and integration tools
Comparative Analysis
ScyllaDB Architecture: Evaluation Matrix
How ScyllaDB engineered by JusDB compares against legacy Apache Cassandra, AWS DynamoDB, and in-house operational engineering.
| Evaluation Vector | JusDB ScyllaDB SRE | Apache Cassandra Legacy | AWS DynamoDB Managed |
|---|---|---|---|
| Engine Architecture & Hardware Utilization | Seastar C++ shard-per-core, zero JVM GC pauses, direct asynchronous NVMe I/O | Java JVM architecture with periodic stop-the-world GC pauses & 3x node overhead | Proprietary serverless cloud architecture subject to strict partition throttling |
| P99 Latency & High-Throughput Scaling | Predictable sub-5ms P99 latency at 1M+ ops/node with dynamic work-stealing priority | P99 tail latencies spike into 50ms–200ms+ during compaction & GC sweeps | Predictable at baseline, but suffers from HTTP request throttling during burst spikes |
| DynamoDB Compatibility (Alternator) | Turnkey Alternator architecture & live migrations reducing AWS DynamoDB bills by 70–90% | No native DynamoDB API support; requires expensive application code refactoring | Native engine with total vendor lock-in and high on-demand read/write request costs |
| Automated Cluster Repair (ScyllaDB Manager) | Continuous non-blocking row-level repairs, automated backup verification & health checks | Requires separate Cassandra Reaper setups with high operator maintenance burden | Internal cloud black-box with zero operational transparency or manual recovery paths |
| 24/7 Production SRE & Sub-15m P1 SLA | Specialized ScyllaDB & NoSQL SREs on-call 24/7 with guaranteed <15m P1 SLA | Internal developers navigating complex tombstone and heap memory stack traces | Standard AWS Support tickets with multi-hour triage queues and generic advice |
| Zero-Downtime Migration & Cassandra Cutover | Dual-write validation, ScyllaDB Migrator pipelines & live zero-downtime cutovers | Complex manual SSTable exports and risky cluster-wide maintenance windows | High egress fees and data export hurdles when attempting to exit AWS |
FAQ
Frequently asked questions about ScyllaDB consulting
Common questions about our ScyllaDB consulting services
How does ScyllaDB compare to Apache Cassandra?
ScyllaDB is a drop-in replacement for Cassandra, rewritten in C++ with a shard-per-core architecture. It delivers 10x better throughput, 10x lower latency, and uses significantly less hardware. ScyllaDB is fully compatible with Cassandra Query Language (CQL) and drivers.
What's the migration path from Cassandra to ScyllaDB?
Migration options include live migration using ScyllaDB Migrator, SSTable-based migration for offline scenarios, and dual-write patterns for zero-downtime transitions. We handle schema conversion, data validation, and application cutover with minimal disruption.
Can ScyllaDB replace DynamoDB using Alternator?
Yes, ScyllaDB Alternator provides a DynamoDB-compatible API, allowing applications to switch from DynamoDB to ScyllaDB with minimal code changes. This eliminates vendor lock-in and can reduce costs by up to 90% while improving performance.
What's ScyllaDB's performance advantage?
ScyllaDB's shard-per-core architecture eliminates the JVM overhead of Cassandra, providing predictable low latency under load. It can handle millions of operations per second on commodity hardware with P99 latencies under 10ms.
How do you handle ScyllaDB security?
We implement comprehensive security including TLS encryption, authentication, role-based access control, audit logging, and network isolation. We also configure ScyllaDB Enterprise features like encryption at rest and LDAP integration.
What monitoring do you provide for ScyllaDB?
We deploy ScyllaDB Monitoring Stack (Prometheus + Grafana) with custom dashboards for cluster health, latency percentiles, compaction, and capacity planning. We also set up alerting for proactive issue detection and resolution.
Get started
Ready to Supercharge Your Database Performance?
Whether you're migrating from Cassandra, escaping DynamoDB lock-in with Alternator, or building new high-performance infrastructure, our ScyllaDB experts will help you succeed.
Explore Our ScyllaDB Services
Explore more ways our ScyllaDB experts can help with your database infrastructure.