When should I use ScyllaDB instead of VoltDB?

High-performance Cassandra-compatible wide-column store with lower latency via C++ implementation. Teams wanting Cassandra semantics with better throughput and without JVM GC pause latency spikes. Workloads where Cassandra's JVM garbage collection causes unpredictable tail latency

When should I use VoltDB instead of ScyllaDB?

In-memory ACID database for high-throughput OLTP with predictable sub-millisecond latency. Financial services and telecom workloads needing thousands of transactions per second. Workloads where stored procedures combine ACID guarantees with extreme write speed

What are the main weaknesses of ScyllaDB?

Cassandra compatibility is not 100%; subtle behavioral differences can surface during migration. Smaller community and ecosystem than Apache Cassandra for tooling and integrations. Self-managed deployment requires Cassandra operational expertise plus ScyllaDB-specific knowledge

What are the main weaknesses of VoltDB?

Expensive commercial licensing for production use at scale. Schema and stored procedure changes require complex, disruptive migration procedures. Not suitable for analytical or OLAP workloads — strictly write-optimized OLTP

ScyllaDB vs VoltDB: Key Differences for Python Data Engineering

Databases & Data Warehouses

ScyllaDB

High-Performance Cassandra Alternative

★ 4.5

AGPL-3.0 (Community)

pip install scylla-driver

VoltDB

In-Memory ACID SQL Database

★ 3.9

AGPL-3.0 (Community) / Commercial

pip install voltdb-client-python

Side-by-Side Comparison

ScyllaDB

VoltDB

ScyllaDB

VoltDB

Best For

✓High-performance Cassandra-compatible wide-column store with lower latency via C++ implementation
✓Teams wanting Cassandra semantics with better throughput and without JVM GC pause latency spikes
✓Workloads where Cassandra's JVM garbage collection causes unpredictable tail latency

✓In-memory ACID database for high-throughput OLTP with predictable sub-millisecond latency
✓Financial services and telecom workloads needing thousands of transactions per second
✓Workloads where stored procedures combine ACID guarantees with extreme write speed

Best For

✓High-performance Cassandra-compatible wide-column store with lower latency via C++ implementation
✓Teams wanting Cassandra semantics with better throughput and without JVM GC pause latency spikes
✓Workloads where Cassandra's JVM garbage collection causes unpredictable tail latency

✓In-memory ACID database for high-throughput OLTP with predictable sub-millisecond latency
✓Financial services and telecom workloads needing thousands of transactions per second
✓Workloads where stored procedures combine ACID guarantees with extreme write speed

Weaknesses

•Cassandra compatibility is not 100%; subtle behavioral differences can surface during migration
•Smaller community and ecosystem than Apache Cassandra for tooling and integrations
•Self-managed deployment requires Cassandra operational expertise plus ScyllaDB-specific knowledge

•Expensive commercial licensing for production use at scale
•Schema and stored procedure changes require complex, disruptive migration procedures
•Not suitable for analytical or OLAP workloads — strictly write-optimized OLTP

Weaknesses

•Cassandra compatibility is not 100%; subtle behavioral differences can surface during migration
•Smaller community and ecosystem than Apache Cassandra for tooling and integrations
•Self-managed deployment requires Cassandra operational expertise plus ScyllaDB-specific knowledge

•Expensive commercial licensing for production use at scale
•Schema and stored procedure changes require complex, disruptive migration procedures
•Not suitable for analytical or OLAP workloads — strictly write-optimized OLTP

License

AGPL-3.0 (Community)

AGPL-3.0 (Community) / Commercial

License

AGPL-3.0 (Community)

AGPL-3.0 (Community) / Commercial

Install

pip install scylla-driver

pip install voltdb-client-python

Install

pip install scylla-driver

pip install voltdb-client-python

Rating

★ 4.5

★ 3.9

Rating

★ 4.5

★ 3.9

Key Features

ScyllaDB

1Cassandra-compatible NoSQL database written in C++ for 10x lower latency
2Shard-per-core architecture eliminates cross-core synchronization overhead
3Drop-in Cassandra replacement — uses the same CQL and drivers
4Compaction strategies optimized for write-heavy workloads
5ScyllaDB Cloud for fully managed deployment on AWS, GCP, and Azure

VoltDB

1In-memory relational database designed for high-throughput OLTP at scale
2Stored procedures in Java executed as single-partition ACID transactions
3Continuous export streams data changes to Kafka or Hadoop in real time
4K-safety replication ensures durability without disk I/O overhead
5Deterministic query execution eliminates lock contention

How Python Data Engineers Use These Tools

ScyllaDB

Python data engineers use ScyllaDB as a Cassandra replacement when latency is critical — the `cassandra-driver` library works unchanged since ScyllaDB is wire-compatible. Engineers migrating from Cassandra to ScyllaDB typically see P99 write latency drop from milliseconds to microseconds without any Python code changes.

VoltDB

Python data engineers interact with VoltDB using the `voltdb` Python client to submit fast transactional operations at microsecond latency. A common use case is a real-time data enrichment pipeline — Python publishes events to VoltDB's stored procedures for in-memory joins and aggregations, then VoltDB's export connector streams results to Kafka for downstream consumers.

More Databases & Data Warehouses Comparisons

Databases & Data Warehouses

MongoDB vs PostgreSQL

Databases & Data Warehouses

PostgreSQL vs Redis

Databases & Data Warehouses

Apache Cassandra vs PostgreSQL

Databases & Data Warehouses

Neo4j vs PostgreSQL

Databases & Data Warehouses

InfluxDB vs PostgreSQL

Databases & Data Warehouses

Elasticsearch vs PostgreSQL

Individual Tool Pages

View ScyllaDB details →View VoltDB details →

Side-by-Side Comparison

ScyllaDB

VoltDB

ScyllaDB

VoltDB

Best For

✓High-performance Cassandra-compatible wide-column store with lower latency via C++ implementation
✓Teams wanting Cassandra semantics with better throughput and without JVM GC pause latency spikes
✓Workloads where Cassandra's JVM garbage collection causes unpredictable tail latency

✓In-memory ACID database for high-throughput OLTP with predictable sub-millisecond latency
✓Financial services and telecom workloads needing thousands of transactions per second
✓Workloads where stored procedures combine ACID guarantees with extreme write speed

Best For

✓High-performance Cassandra-compatible wide-column store with lower latency via C++ implementation
✓Teams wanting Cassandra semantics with better throughput and without JVM GC pause latency spikes
✓Workloads where Cassandra's JVM garbage collection causes unpredictable tail latency

✓In-memory ACID database for high-throughput OLTP with predictable sub-millisecond latency
✓Financial services and telecom workloads needing thousands of transactions per second
✓Workloads where stored procedures combine ACID guarantees with extreme write speed

Weaknesses

•Cassandra compatibility is not 100%; subtle behavioral differences can surface during migration
•Smaller community and ecosystem than Apache Cassandra for tooling and integrations
•Self-managed deployment requires Cassandra operational expertise plus ScyllaDB-specific knowledge

•Expensive commercial licensing for production use at scale
•Schema and stored procedure changes require complex, disruptive migration procedures
•Not suitable for analytical or OLAP workloads — strictly write-optimized OLTP

Weaknesses

•Cassandra compatibility is not 100%; subtle behavioral differences can surface during migration
•Smaller community and ecosystem than Apache Cassandra for tooling and integrations
•Self-managed deployment requires Cassandra operational expertise plus ScyllaDB-specific knowledge

•Expensive commercial licensing for production use at scale
•Schema and stored procedure changes require complex, disruptive migration procedures
•Not suitable for analytical or OLAP workloads — strictly write-optimized OLTP

License

AGPL-3.0 (Community)

AGPL-3.0 (Community) / Commercial

License

AGPL-3.0 (Community)

AGPL-3.0 (Community) / Commercial

Install

pip install scylla-driver

pip install voltdb-client-python

Install

pip install scylla-driver

pip install voltdb-client-python

Rating

★ 4.5

★ 3.9

Rating

★ 4.5

★ 3.9

Key Features

ScyllaDB

1Cassandra-compatible NoSQL database written in C++ for 10x lower latency
2Shard-per-core architecture eliminates cross-core synchronization overhead
3Drop-in Cassandra replacement — uses the same CQL and drivers
4Compaction strategies optimized for write-heavy workloads
5ScyllaDB Cloud for fully managed deployment on AWS, GCP, and Azure

VoltDB

1In-memory relational database designed for high-throughput OLTP at scale
2Stored procedures in Java executed as single-partition ACID transactions
3Continuous export streams data changes to Kafka or Hadoop in real time
4K-safety replication ensures durability without disk I/O overhead
5Deterministic query execution eliminates lock contention

How Python Data Engineers Use These Tools