Sold by: ScyllaDB, Inc
Deployed on AWS
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ScyllaDB Enterprise NoSQL database
4.5
Overview
ScyllaDB Enterprise is the high-performance NoSQL database for real-time big data workloads. It is a wide-column store with APIs compatible with Apache Cassandra CQL and Amazon DynamoDB. ScyllaDB Enterprise is self-tuning upon installation and self-optimizing in production, which means users get optimal performance without spending time constantly tweaking the system. It just runs consistently fast, with consistent low latency. ScyllaDB is designed to take full advantage of NUMA multiprocessor architectures and fast storage, such as those found in AWS I3, i3en, and i4i series instances.
Highlights
- Build highly scalable, highly performant NoSQL-based applications that can support high-throughput (millions of transactions per second per database node) and maintain consistent low single-digit millisecond latencies.
- APIs compatible with Apache Cassandra CQL and Amazon DynamoDB.
- With ScyllaDB hardware efficiency and predictable pricing, users reduce their TCO up to 70% without compromising performance.
Details
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Delivery method
Delivery option
64-bit (x86) Amazon Machine Image (AMI)
Latest version
Operating system
Ubuntu 22.04
Deployed on AWS
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Pricing
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Try this product free for 7 days according to the free trial terms set by the vendor. Usage-based pricing is in effect for usage beyond the free trial terms. Your free trial gets automatically converted to a paid subscription when the trial ends, but may be canceled any time before that.
Pricing is based on actual usage, with charges varying according to how much you consume. Subscriptions have no end date and may be canceled any time. Alternatively, you can pay upfront for a contract, which typically covers your anticipated usage for the contract duration. Any usage beyond contract will incur additional usage-based costs.
Additional AWS infrastructure costs may apply. Use the AWS Pricing Calculator to estimate your infrastructure costs.
Dimension | Cost/hour |
|---|---|
i3.4xlarge Recommended | $1.63 |
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Delivery details
64-bit (x86) Amazon Machine Image (AMI)
Amazon Machine Image (AMI)
An AMI is a virtual image that provides the information required to launch an instance. Amazon EC2 (Elastic Compute Cloud) instances are virtual servers on which you can run your applications and workloads, offering varying combinations of CPU, memory, storage, and networking resources. You can launch as many instances from as many different AMIs as you need.
Version release notes
Additional details
Usage instructions
Resources
Vendor resources
Support
Vendor support
Scylladb Enterprise support ensures that users have access to the engineers who develop Scylla via the channels they prefer - the web support, email, Slack, etc. https://www.scylladb.com/scylladb-support-policy/
For additional information, custom pricing, or a private contract, please contact info@scylladb.com .
AWS infrastructure support
AWS Support is a one-on-one, fast-response support channel that is staffed 24x7x365 with experienced and technical support engineers. The service helps customers of all sizes and technical abilities to successfully utilize the products and features provided by Amazon Web Services.
Updated weekly
By ScyllaDB, Inc
By MongoDB, Inc
By Supported Images
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In Databases, Databases & Analytics Platforms
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Sentiment is AI generated from actual customer reviews on AWS and G2
Functionality
Ease of use
Customer service
Cost effectiveness
Positive reviews
Mixed reviews
Negative reviews
AI generated from product descriptions
Wide-Column Store Architecture
NoSQL database with wide-column store design supporting high-throughput workloads and real-time big data processing
API Compatibility
Compatible with Apache Cassandra CQL and Amazon DynamoDB APIs
Self-Tuning and Self-Optimizing
Automatic performance tuning upon installation and continuous optimization in production without manual system configuration
NUMA Architecture Optimization
Designed to leverage NUMA multiprocessor architectures and fast storage devices including AWS I3, i3en, and i4i series instances
Low-Latency Performance
Delivers consistent single-digit millisecond latencies with support for millions of transactions per second per database node
Native Vector Search Integration
MongoDB Atlas integrates native vector search directly into the operational database, enabling RAG and agentic AI solutions without requiring separate search infrastructure.
Flexible Document Model
Supports storage and synchronization of structured, unstructured, and semi-structured data types with dynamic schema capabilities for AI-driven applications.
Multi-Workload Unification
Consolidates operational, analytical, and AI workloads within a single database platform.
Industry Compliance Standards
Complies with HIPAA, GDPR, ISO 27001, and PCI DSS standards with built-in security features and encryption.
Elastic Scalability
Supports both vertical and horizontal scaling with configurable cluster configurations to accommodate varying application demands.
Peer-to-Peer Architecture
Utilizes a peer-to-peer architecture enabling horizontal scalability without any single point of failure across distributed systems.
Tunable Consistency Levels
Supports customizable consistency levels allowing developers to balance performance and data consistency based on specific workload requirements.
Schema-Free Data Model
Handles structured, semi-structured, and unstructured data with a schema-free design that adapts to diverse application needs.
Multi-Node Data Distribution
Supports data distribution across multiple nodes providing resilience against hardware failures and continuous operation without downtime.
Pre-Configured Deployment
Comes pre-configured with best practices on Ubuntu 22.04 LTS enabling rapid deployment and seamless integration with AWS services.
Validated by AWS Marketplace
FedRAMP
GDPR
HIPAA
ISO/IEC 27001
PCI DSS
SOC 2 Type 2
No security profile
-
No security profile
Standard contract
No
Customer reviews
Satendra S.
High performance and scalable NoSQL database.
Reviewed on Mar 11, 2026
Review provided by G2
What do you like best about the product?
I loved the performance and scalability while ingesting or retrieving high amount of data.
What do you dislike about the product?
I am still learning about it so nothing so serious issues I found till now though I would love to see more documentations around configurations and operational management.
What problems is the product solving and how is that benefiting you?
Our data is evolving, scylladb solving performance and scalability issues. it has drastically improved the query latency when we deal with nested/raw data. it best fit for our near real-time data processing framework.
Abhishek K.
Seamless Cassandra Transition with High Throughput
Reviewed on Mar 11, 2026
Review provided by G2
What do you like best about the product?
I use ScyllaDB to store high throughput IoT pings, and it effectively handles high throughput ingestion. The transition to ScyllaDB from Cassandra was made easier because it is very much compatible with Cassandra, facilitating a smoother migration. I would highly recommend ScyllaDB to others, rating it a 10 out of 10.
What do you dislike about the product?
No
What problems is the product solving and how is that benefiting you?
I use ScyllaDB for high throughput ingestion, and migrating from Cassandra was easier due to its compatibility.
Sayanta B.
One of the best high performance databases for scaling
Reviewed on Mar 11, 2026
Review provided by G2
What do you like best about the product?
ScyllaDB is one of the best of its kind when it comes to its performance and efficient resource utilization. Its ability to use modern hardware and deliver very high throughput with extremely low latency is very impressive. It seamlessly handles large volumes of data and concurrent requests while performing better than other traditional NoSQL databases. Plus, it is easy to integrate with the existing workflows.
What do you dislike about the product?
While it is such a great database for handling large chunks of data, the operational challenge can be a bottleneck for newly distributed teams.
What problems is the product solving and how is that benefiting you?
In our organization, we handle large volume of sensitive data and ScyllaDB helped handle such large-scale high throughput data with minimal latency. The best part is that it uses its shard-per-core architecture that allows it to fully utilize modern multi-core CPUs. Thus, the performance becomes positively predictable even under heavy load. We don't have to spend our time and efforts in constant scaling of infrastructure because of its system responsiveness. Its stable performance enables us to operate smoothly with real-time applications and data-intensive services.
Jayesh S.
Handles High Write Loads with Ease
Reviewed on Mar 11, 2026
Review provided by G2
What do you like best about the product?
I find ScyllaDB easy to query and capable of ingesting a high volume of data. I receive about 50K insert queries per second, along with subsequent update queries on SMS delivery reports, and it's handled well by ScyllaDB. Setting up the initial multi-data center cluster was also very easy.
What do you dislike about the product?
I don't like altering the schema or querying on non-primary index data without using allow filtering.
What problems is the product solving and how is that benefiting you?
I use ScyllaDB for handling heavy writes and updates per second. It's easy to query and ingest high data volumes, managing 50K/s insert queries and updates on SMS DLRs effectively.
Deeksha R.
Solid Vector Search Support, Room to Grow
Reviewed on Mar 11, 2026
Review provided by G2
What do you like best about the product?
vector search support
rest api compatibility
rest api compatibility
What do you dislike about the product?
integrating with complex legacy product like the one i work on , the cost insreases .My product still uses wsssdl way of api communication
What problems is the product solving and how is that benefiting you?
as no data is shared , its ideal for our saas product which is based on microservice architecture . this helps is moving from distributed monolith arch to actual microservice arch