mongodb vs postgresql performance

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Redis, MongoDB paging/ranking performance comparison at large offsets

skip seriously affects performance, should be strictly avoid the special large skip operation.Redis=redis.new (:d River=>:hiredis) benchmark.bmbmdo|x| X.report ("Redissmall") do100.timesdo|i| start=i*20redis.zrevrange (Lids.sample, start,start+20,:with_scores=>true) end endx.report ("Redismedium") do100.timesdo |i|start=i*1000 redis.zrevrange (lids.sample,start,start+20,:with_scores=> true) endendx.report ("Redislarge") do 100.timesdo|i|start=i* 1000

A complete list of MongoDB performance tests with hundreds of millions of data records

it by the date field of another index (the index is created in reverse order, and the sorting is also in reverse order ), and the performance of 10 records is returned after the skip100 records. The impact of skip and order on the performance is measured. 7) query the performance of 100 records (that is, KB) (no sorting and no conditions). This test is to test

Performance testing of hundreds of millions of MongoDB data volumes

, and the sorting is also in reverse order ), and the performance of 10 records is returned after the skip100 records. The impact of skip and order on the performance is measured. 7) query the performance of 100 records (that is, KB) (no sorting and no conditions). This test is to test the performance impact of query

Considerations for MongoDB production environment performance and reliability

This article translates MongoDBProductionNotes in MongoDBManuel. This section focuses on considerations that affect performance and reliability in the production environment, This article is to translate the MongoDB Production Notes section in MongoDB Manuel. This section focuses on considerations that affect performance

Performance testing of MONGODB billion-level data volume

The performance test of MONGODB billion data volume was carried out, and the following items were tested:(All inserts are single-threaded and all reads are multithreaded)1) Normal insertion performance (the inserted data is about 1KB per piece)2) Bulk Insert performance (using the official C # client's Insertbatch), wh

MongoDB and MySQL Insert, query performance test

of data is about 1 K. Remember that the method of this test is to generate 100 million data in memory before performing the insert operation. Fortunately, the memory of the test machine is large enough to save so much data. 3. Insert data into the database in the following four modes, and when each 1000 data is inserted, the time of the moment is written to a fixed file: A) specify _ID as the MD5 value of 1–100,000,000 in M

Performance testing of hundreds of millions of Mongodb data volumes

reverse order ), and the performance of 10 records is returned after the Skip100 records. The impact of Skip and Order on the performance is measured. 7) query the performance of 100 records (that is, KB) is not sorted and there are no conditions). This test is the impact of query results of large data volumes on the perform

MongoDB 3.2 WiredTiger storage engine performance test

MongoDB 3.2 WiredTiger storage engine performance test MongoDB 3.2 was recently released. It uses WiredTiger as its default storage engine. Over the past five years, MongoDB has developed rapidly from its birth to its popularity. MongoDB 3.0 began to support the "pluggable s

MongoDB-level data insert, query, and delete performance tests (without or without indexing)

Let's take a look at the testing machine performance (64bit ): ^_^[root@:~]#grep "model name" /proc/cpuinfo | cut -f2 -d: Intel(R) Xeon(R) CPU E5606 @ 2.13GHz Intel(R) Xeon(R) CPU E5606 @ 2.13GHz Intel(R) Xeon(R) CPU E5606 @ 2.13GHz Intel(R) Xeon(R) CPU E5606 @ 2.13GHz Intel(R) Xeon(R) CPU E5606 @ 2.13GHz Intel(R) Xeon(R) CPU E5606 @ 2.13GHz Intel(R) Xeon(R) CPU E5606 @ 2.13G

Testing MongoDB Shard cluster performance using YCSB

1. Test ToolsThis test chooses YCSB (Yahoo! Cloud System Benchmark) as the test Client tool. YCSB is a NoSQL test tool for Yahoo Open source, used to test the performance of a variety of NoSQL, project address: Https://github.com/brianfrankcooper/YCSB. The project's MongoDB directory has detailed installation and testing methods. YCSB supports common NoSQL database reads and writes, such as inserting, modif

[CACTI] MongoDB performance monitoring combat

]# php ss_get_by_ssh.php--type mongodb--host 10.254.3.62--port2 30000--items JC,JDJc:4 jd:5497683968 5, generate the monitor diagram In the interface, select "Device", select the MongoDB server Connection "3.x2_mongodb", then select "Create Graphs for this Host" in the upper right corner, select the MongoDB service item in the dropdown box after "Graph Types", Yo

MongoDB paging query method and Performance

MongoDB paging query method and Performance I have been a little busy recently. There are a lot of things to summarize. In fact, there should be four, five, and six Redis series... however, Redis in Action has not been completed yet. I will summarize it later. Otherwise, it will be too watery. Sorry, readers. Since the last time in Redis, it was a bit of an entry into Nosql products. This will change the di

Performance Comparison of NoSQL databases MongoDB, Redis, and Tokyo Tyrant

We are going to perform a simple test on reading and writing MongoDB, Redis, and Tokyo Tyrant. To perform a fair test, we need to understand the implementation mechanism behind them. Below are some comparisons:Comparison of storage implementation:* Memory File Image (Memory-File Mapping) Redis, MongoDB* File + Cache Tokyo Tyrant* Memory: Redis, Tokyo TyrantKey/Value index format:* B + Tree:

[Original] MongoDB, handlersocket and MySQL Performance Test and result analysis

handlersocket. Therefore, we can see that the number of QPS is significantly greater than the number of TPS, and batch insert operations significantly improve the overall performance. MongoDB adopts the method of merging operations internally. Data is first stored in the memory and then flushed to the disk. Therefore, from the test data, we can see that the TPS curve slope is very high: Sometimes the T

Considerations for MongoDB production environment performance and reliability

This article is to translate the MongoDB Production Notes section in MongoDB Manuel. This section focuses on considerations that affect performance and reliability in the production environment, and deserves the attention of those who are deploying MongoDB. This article describes in detail the key system configurations

Real MongoDB Performance

I recently started to study MySQL and MongoDB and found that there is not much information in this area. Especially when it comes to ideasArticle, Too few. Some articles on comparative testing are basically blind tests. The testing methods are tested on the horse, and the conclusion is basically that nosql has no value. Let me borrow the sentence from Russell Smith: It's not MongoDB, but you don't under

MongoDB-level data Insert, Query, and Delete performance tests

MongoDB-level data Insert, Query, and Delete performance tests (without or without indexing) Let's take a look at the testing machine performance (64bit ): Performance_^ [root @: ~] # Grep"Model name"/Proc/cpuinfo | cut-f2-d: Intel (R) Xeon (R) CPU E5606 @ 2.13 GHz Intel (R) Xeon (R) CPU E5606 @ 2.13 GHz Intel (R) Xeon (R) CPU E5606 @ 2.13 GHz Intel (R)

Ignore: MongoDB's JavaScript Performance

SpiderMonkey Mongo js shell After I have compiled the Mongodb v8 version, I will compare and test the four environments. Compile mongodb + v8 In OpenSUSE11.4, it is easy to use the linux package management tool to prepare the compiling environment: # Installed Package: g ++ subversion git python Code highlighting produced by Actipro CodeHighlighter (freeware)http://www.CodeHighlighter.com/--> Sudo zypper

MongoDB Query Performance Optimization verification and verification _mongodb

Conclusion: 1, 200w data, reasonable use of the index case, a single stationid under 4w data. MongoDB Query and sorting performance ideal, no regular when the client can complete the query in 600ms+, qps300+. When there is a regular client can complete the query in 1300ms+, qps140+. 2, MongoDB count performance is re

18 principles for MongoDB boost performance (development design phase)

MongoDB is a high-performance data, but in the process of use, you will occasionally encounter some performance problems. MongoDB is relatively new compared to other relational databases, such as SQL Server, MySQL, and Oracle, and many people are not familiar with it, so many developers, DBAs tend to focus on the imple

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