Today, Thumbtack Technology published a blog post highlighting the final results of the NoSQL benchmark (enlace).

In June, the databases were benchmarked on 4 physical servers. I could see MongoDB and DataStax in the rearview mirror (enlace). Then, the databases were benchmarked on 4, 6, and 8 physical servers.

The performance tests were executed with two workloads.

  • Read Intensive (95% read / 5% write)
  • Balanced (50% read / 50% write)

Intensivo de lectura

MongoDB scaled from 130K ops / second with 4 servers to 227K ops / second with 8 servers. The average latency was less than a millisecond. The latency is great, the throughput is no.

Apache Cassandra (DataStax) scaled from 60K ops / second with 4 servers to 99K ops / second with 8 servers. The average latency was below 3ms. The latency is not good, neither is the throughput.

Couchbase Server scaled from 903K ops / second with 4 servers to 1.71 million ops / second with 8 servers. The average latency was less than a millisecond. The latency is great, the throughput is great.

Equilibrado

MongoDB scaled from 50K ops / second with 4 servers to 85K ops / second with 8 servers. The average latency was less than a 2ms. The latency is pretty good, the throughput is pretty bad.

Apache Cassandra (DataStax) scaled from 53K ops / second with 4 servers to 89K ops / second with 8 servers. The average latency was below a millisecond. The latency is great, the througput is no.

Couchbase Server scaled from 800K ops / second with 4 servers to 1.24 million ops / second with 8 servers. The average latency was less than two milliseconds. The latency is pretty good, the throughput is great.

Conclusión

Apache Cassandra (DataStax) meets low latency requirements for write requests, at low throughput. It’s not engineered for read performance. It does not leverage memory effectively (enlace). Apache Cassandra was engineered for an era when servers had little memory and spinning disks.

MongoDB meets low latency requirements for read requests, at low throughput. It’s not engineered for write performance. It’s limited by a master / slave topology, database-wide locking (one per db per instance), and more. MongoDB was engineered for… well, I’m not sure what it was engineered for.

Couchbase Server meets low latency requirements for read y write requests, at cualquier throughput. Unlike MongoDB, it doesn’t have topology and locking issues. Unlike Apache Cassandra, it leverages memory effectively with a integrated, managed object cache. Couchbase Server was engineered for read y write performance.

I can’t see MongoDB and DataStax in the rearview. Not any more. Where art thou?

It’s all in the white paper (aquí).

See Doug’s take on the benchmark results (aquí).

Hacker News (enlace)
Reddit (enlace)

Autor

Publicado por Shane Johnson, Director de Marketing de Producto, Couchbase

Shane K Johnson fue Director de Marketing de Producto en Couchbase. Antes de Couchbase, ocupó varios puestos en desarrollo y evangelización con formación en Java y sistemas distribuidos. Ha sido consultor de organizaciones de los sectores financiero, minorista, de las telecomunicaciones y de los medios de comunicación para diseñar e implantar arquitecturas basadas en sistemas distribuidos para datos y análisis.

1 Comentarios

  1. We may need a Couchbase section if/after we develop content for that NoSQL DB, too.

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