ScyllaDB · CQL · Alternator · SeastarScyllaDB, Cassandra speed without the JVM.
In short: ScyllaDB is a high-performance, distributed NoSQL wide-column database rewritten in C++ as a drop-in replacement for Apache Cassandra. Its shard-per-core architecture eliminates JVM overhead to deliver predictable low latency and far higher throughput, while staying compatible with Cassandra's CQL and offering a DynamoDB-compatible API via Alternator.
ScyllaDB consulting for distributed databases, Cassandra migration, cluster architecture, and Alternator deployment. Cassandra comparisons are benchmarked on the target workload before a recommendation.
JUSDB_SCYLLA_PRODScyllaDB 6 · shard-per-core
Masterless ring · RF=3 · tablets
0.00M
0.3ms
98.0%
96.0%
[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
Illustrative operating profile - example fleet and outcome figures, not audited customer results.
0+
ScyllaDB Nodes Managed
0.99%
Uptime SLA
0M+
Ops/sec at Scale
0%
Cost Savings vs Cassandra
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
Cassandra-to-ScyllaDB migration with compatibility checks, data validation, a measured cutover window, and rollback planning.
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.
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
Illustrative target3×
Throughput / node
70%
Fewer nodes
Illustrative workload optimization scenarios
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.
Resilience by design. 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. We test failure modes against the availability and recovery objectives agreed for the deployment.
A hot-shard P1, handled against the contracted response target.
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)
Move to ScyllaDB with a validated cutover
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.
Technologies We Work With
Complete ScyllaDB ecosystem and integration tools
Frequently asked questions about ScyllaDB consulting
Common questions about our ScyllaDB consulting services
How does ScyllaDB compare to Apache Cassandra?
ScyllaDB is a Cassandra-compatible database written in C++ with a shard-per-core architecture. ScyllaDB publishes benchmark comparisons against Cassandra, but achievable throughput, latency, hardware use, CQL coverage, and driver behavior should be validated on the target workload.
What's the migration path from Cassandra to ScyllaDB?
Migration options include ScyllaDB Migrator, SSTable-based migration for offline scenarios, and dual-write patterns for low-interruption transitions. We handle schema conversion, data validation, and a workload-tested application cutover with rollback criteria.
Can ScyllaDB replace DynamoDB using Alternator?
ScyllaDB Alternator provides a DynamoDB-compatible API, but application compatibility, operational ownership, cost, latency, and throughput must be tested against the target workload before choosing a migration.
What's ScyllaDB's performance advantage?
ScyllaDB uses a shard-per-core architecture rather than Cassandra's JVM model. Published benchmarks describe high-throughput, low-latency behavior, but achievable p99 latency, throughput, and hardware efficiency must be measured on the target data model and infrastructure.
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.
ScyllaDB information, checked against primary documentation
JusDB reviews technology-specific claims against the vendor or project's official documentation. Performance examples without a linked case study are labeled illustrative; actual results depend on workload, data model, version, topology, infrastructure, and test method.
Technically reviewed by the JusDB Database Reliability Engineering team on .
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