November 6-7 | Pullman San Francisco Bay Hotel
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November 6-7 | Pullman San Francisco Bay Hotel
Super Early Bird Savings: Register by July 31st and Save 50% on 2-Day Pass
Samsung Benchmark:
Throughput of ScyllaDB vs Apache Cassandra Using 2TB Data for Different YCSB Workloads
YCSB Benchmark:
Scylla vs Apache Cassandra Using only 3 Scylla Nodes
AWS c3.2xlarge:
Throughput Results of Scylla 1.6 vs Apache Cassandra 3.0 Using Amazon Web Server c3.2xlarge
Lockless implementation and an independent memory management stack remove the inefficient reliance on JVM or Linux page cache to deliver consistently low latency.
Automatic failover and replication across multiple nodes and data-centers makes for reliable fault tolerance.
Written in C++ to squeeze every bit of performance from hardware and allow up to 1,000,000 read/write operations per node.
Auto-sharding, homogeneous servers, and native multi-datacenter implementation allow seamless linear scaling without compromising on application downtime or performance.
Apache Cassandra’s wire protocol, a rich polyglot of drivers, and integration with Spark, Presto, and Graph tools make for resource-efficient and performance-effective coding.
ScyllaDB has been open sourced since day one and is backed by a growing community of contributors.
Workload conditioning provides an umbrella of dynamic scheduling algorithms to minimize database operation latency jitter and reduce compaction streaming and repair time.
C++ framework boots effectiveness to capture up to 10x throughput over existing infrastructure.
Fully automated and dynamic tuning effectively manages internal resource, requires zero configuration, and enhances performance straight out of the box.
| What makes “a good” vs. a great database deployment? | Apache Cassandra | Scylla |
|---|---|---|
| High Availability | 
Cassandra: Multi-region and fault tolerant |
Scylla: Multi-region and fault tolerant |
| High Scalability |
Cassandra: Homogeneous nodes scale to hundreds of nodes per cluster |
Scylla: Homogeneous nodes scale to hundreds of nodes per cluster. Additionally, Scylla scales up with the number of cores in our server |
| Low Latency | 
Cassandra: Unpredictable and unbounded latency, mainly the result of the JVM’s GC |
Scylla: C++, shared-nothing and lockless novel design allows < 1 millisecond tail latency |
| High Throughput |
Cassandra: Limited per-node performance. Cannot fully exploit the disk/memory/cpus |
Scylla: Fully asynchronous core engine with shard-per-core architecture allows perfect scale-up |
| Less Management |
Cassandra: Intricate tuning, endless compactions and GC storms makes it hard to maintain |
Scylla: Out-of-the-box tuning, isolation and SLA between background and foreground jobs free DevOps time during day and lets them sleep at night |
ScyllaDB Announces Support for IBM Power Systems
June 6, 2018
NoSQL Database Company ScyllaDB Raises $10 Million Series C Led By TLV Partners
April 25, 2018 | Crunchbase
7 Design Decisions that Apache Cassandra’s Successor is Built On
April 4, 2018 | Open Source For You
ScyllaDB is better than Cassandra, and here’s why
April 1, 2018 | EPeak
Numberly on Evaluating Scylla for Production
March 2, 2018 | Ultrabug
Does It Make Sense to Do Big Data with Small Nodes?
February 22, 2018 | Inside Big Data
Scylla Eyes Cassandra’s NoSQL Workloads
February 13, 2018 | Datanami
Monster performance from IBM Compose for ScyllaDB powers IBM Cloud’s service catalog
February 8, 2018 | IBM Cloud Blog
A rock and a hard place: Between ScyllaDB and Cassandra
October 24, 2017 | ZDNet
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