ArangoDB vs ScyllaDB Comparison: Reviews, Features, Pricing & Alternatives in 2026

Detailed side-by-side comparison to help you choose the right solution for your team

Updated May 2026 8 min read

ArangoDB

0.0 (0 reviews)

ArangoDB is a graph database that combines graphs, documents, and key-values in a single engine to simplify your data architecture and accelerate complex application development.

Starting at Free
Free Trial 14 days
VS

ScyllaDB

0.0 (0 reviews)

ScyllaDB is a high-performance NoSQL database built for data-intensive applications that require ultra-low latency, high throughput, and horizontal scalability to handle massive workloads across distributed cloud environments.

Starting at Free
Free Trial 30 days

Quick Comparison

Feature ArangoDB ScyllaDB
Website arangodb.com scylladb.com
Pricing Model Freemium Freemium
Starting Price Free Free
FREE Trial ✓ 14 days free trial ✓ 30 days free trial
Free Plan ✓ Has free plan ✓ Has free plan
Product Demo ✓ Request demo here ✓ Request demo here
Deployment cloud on-premise desktop cloud on-premise
Integrations Kubernetes Docker Terraform Tableau Grafana Python JavaScript Java Go Spark Spark Kafka Presto Elasticsearch Grafana Prometheus Kubernetes Terraform
Target Users small-business mid-market enterprise mid-market enterprise
Target Industries finance healthcare technology ad-tech gaming iot
Customer Count 0 0
Founded Year 2012 2012
Headquarters San Francisco, USA Palo Alto, USA

Overview

A

ArangoDB

ArangoDB is a flexible graph database that lets you store and query data as documents, graphs, or key-values within a single engine. You can build complex applications without the headache of managing multiple database technologies or worrying about data consistency across different systems. By using one query language, AQL, you can perform joins, graph traversals, and geo-spatial lookups in a single request.

You can scale your deployments from a single instance to massive clusters using the ArangoGraph Insights Platform, their fully managed cloud service. It is particularly effective if you are dealing with highly connected data, such as fraud detection systems, knowledge graphs, or recommendation engines. The platform helps you reduce architectural complexity while maintaining high performance for deep-link analytical queries.

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ScyllaDB

ScyllaDB provides you with a distributed NoSQL database designed for high-throughput and low-latency applications. It uses a shared-nothing architecture that scales linearly with your hardware, allowing you to handle millions of operations per second without the performance bottlenecks found in traditional systems. You can deploy it as a fully managed cloud service or manage it yourself on-premise while maintaining full compatibility with Cassandra and DynamoDB APIs.

You can eliminate the overhead of garbage collection and complex JVM tuning because the system is written in C++. This allows you to achieve predictable performance even under heavy loads, making it ideal for real-time analytics, ad tech, and IoT applications. Whether you are migrating from legacy NoSQL or building a new high-scale service, you get a database that maximizes your infrastructure efficiency and reduces your total cost of ownership.

Overview

A

ArangoDB Features

  • Multi-Model Engine Combine graph, document, and key-value data models in one place to simplify your backend infrastructure.
  • ArangoDB Query Language Use a single, human-readable language to perform complex graph traversals and document joins in one query.
  • SmartGraphs Scale your graph data across multiple nodes while maintaining high performance for complex, deep-link traversals.
  • Integrated Search Retrieve information quickly with a built-in full-text search engine that works natively with your stored data.
  • ArangoGraph Cloud Deploy and manage your databases in a fully automated cloud environment across major providers like AWS and Azure.
  • Microservices Framework Build and run data-intensive microservices directly inside the database using the integrated Foxx JavaScript framework.
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ScyllaDB Features

  • Shared-Nothing Architecture. Scale your database linearly across multiple nodes and cores to handle massive traffic spikes without losing performance.
  • Cassandra & DynamoDB Compatibility. Migrate your existing applications easily using familiar APIs and drivers without rewriting your entire application code.
  • Autonomous Operations. Let the database handle complex tasks like compaction, repair, and caching automatically to reduce your manual maintenance effort.
  • Workload Prioritization. Run your real-time transactions and analytical queries on the same cluster without them interfering with each other's performance.
  • C++ Performance Engine. Eliminate unpredictable latency spikes caused by Java garbage collection for more consistent response times across your application.
  • Multi-Cloud Deployment. Deploy your clusters across AWS, GCP, or Azure to ensure high availability and avoid vendor lock-in for your data.

Pricing Comparison

A

ArangoDB Pricing

Community Edition
$0
  • Open-source core engine
  • Multi-model support
  • AQL query language
  • Self-managed deployment
  • Community-based support
S

ScyllaDB Pricing

Free Tier
$0
  • One small cluster
  • Limited storage capacity
  • Community support
  • Basic monitoring tools
  • Standard backup options

Pros & Cons

M

ArangoDB

Pros

  • Unified query language simplifies complex data operations
  • Excellent performance for deep graph traversals
  • Flexible schema allows for rapid prototyping
  • Active community and helpful documentation
  • Eliminates the need for multiple database types

Cons

  • Learning curve for mastering AQL syntax
  • Memory consumption can be high for large datasets
  • Cloud pricing can become complex to predict
A

ScyllaDB

Pros

  • Exceptional performance and ultra-low latency
  • Significant reduction in server footprint and costs
  • Seamless migration from Apache Cassandra
  • Excellent support for high-concurrency workloads
  • Predictable performance without JVM tuning

Cons

  • Steep learning curve for advanced configurations
  • Smaller community compared to older NoSQL databases
  • Limited documentation for very niche use cases
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