NoSQL数据库性能评估

jieforest

Load phase

During the first stage of the test, the load phase, we uploaded 100,000,000 records of 1 Kb each to every data store. YCSB measured the average throughput in operations per second and average latency of operations in milliseconds. The next diagram displays the results of the load phase:


Figure 2: The results of the load phase. Source: Altoros

jieforest

HBase demonstrated the lowest throughput, probably because we turned on the auto-flash mode. This mode ensures that each operation that creates a record will be sent from the client to the server and then persisted to the database. HBase also supports an alternative mode that uses additional cash on the client side. When the client is out of client cache it sends data from the cash to the server. In this alternative mode, HBase saves data to disk in batches.

As we expected, Cassandra demonstrated excellent results with almost 18,000 operations per second. This is due to Cassandra’s architecture. It simultaneously updates data in memory and writes it to the transaction journal on the disk. This guarantees data persistency should a node crash.

The number of operations per second in MongoDB’s results was pretty close to that of Hbase - the average latency was around seven milliseconds at 13,000 operations per second.

In this particular test, all data was loaded in a single iteration, but insert, update, read, and scan operations in the transaction phase of the test were performed in five iterations for each workload (for every database).

jieforest

It should be noted that many of the diagrams with test results demonstrate that database performance is limited and starts to decline at a certain throughput level. Also we need to mention that we used Amazon AWS and network storage which could potentially influence the results.

Workload A

Workload A includes read and update operations in a ratio of 50/50. It simulates an e-commerce application. This slide shows the results of update operations.


Figure 3: The results of update operations in Workload A. Source: Altoros

jieforest

Cassandra and HBase demonstrated good performance with a throughput below 20 milliseconds.

MongoDB’s latency increased substantially as we increased the workload. At 100 operations per second all the four databases had similar performance. But when the workload reached 1,500 operations per second, MongoDB’s latency increased to 100 milliseconds.

The next diagram shows results of read operations in Workload A.

jieforest

Figure 4: Figure 4. The results of read operations for Workload A. Source: Altoros

All the graphs are very different because reads and updates were randomly distributed. The results for read operations in Workload A were more or less similar in all the tested solutions. The difference in latencies was insignificant, within a range of 15-30 milliseconds.

Workload B

Workload B is read-mostly with 95% of reads and only 5% of updates. It simulates content tagging when adding a tag is an update, but most other transactions are reads. Here are the results for update operations in workload B.

jieforest

Figure 5. The results of update operations for Workload B. Source: Altoros

Cassandra demonstrates a very low latency, but her performance is limited to 1200 operations per second. With HBase, the latency increases evenly as the workload grows. The behavior of MongoDB is similar to the previous test where the latency increased together with the throughput.

The next slide shows the results of read operations that make up 95% of Workload B.