mongodb vs postgresql performance

statements to reduce the cost of committing a transaction;Use cluster when extracting multiple records from an index;Use limit when extracting part of a record from a query result;Use pre-compiled queries (Prepared query);Use analyze to maintain accurate optimization statistics;Regular use of VACUUM or pg_autovacuumDelete indexes first when making large amounts of data changes (then rebuilding indexes)2, program ExperienceCheck the program, whether the use of connection pool, if not used, as so

Tips for improving PostgreSQL Performance In a (poor) PostgreSQL query, only a small change is required (ANY (ARRAY [...]). to ANY (VALUES (...))) the query time can be reduced from 20 s to 0.2 s. From the simplest use of explain analyze, to the use of EXPLAIN s community, there will be a hundred times of learning time investment to return. Use ipvs to monitor sl

PostgreSQL Performance Monitoring ToolsHttps://github.com/CloudServer/postgresql-perf-toolsThis package includes three useful scripts aimed to help to pinpoint performance issues on systems with PostgreSQL as data Base backend.All Scritps is written in Python. Requirements:

PostgreSQL provides some functions to help improve performance. There are several main aspects. 1. Use the explain command to view the execution plan. In the previous blog PostgreSQL provides some functions to help improve performance. There are several main aspects. 1. Run the EXPLAIN command to view the execution pla

PostgreSQL supports hstore to store data such as Key->value, which is in fact similar to array or JSON type. Efficient indexing is essential to the efficient use of this type of data. Let's take a look at the performance issues of two different types of indexes for the same retrieval request today.If we had such an original table. There is a Btree index based on the Str1 field.t_girl=# \d Status_check;

MongoDB Performance Analysis method:explain ()To demonstrate the effect, let's start by creating a record with 2 million documents. (My own computer took about 15 minutes to insert the completed.) If you want to plug in more documents It's okay, just be patient and wait. ）1 for (var i=0;i) {2 db.person.insert ({"Name": "Ryan" +i, "age": i}); 3 }After MongoDB

1. Use EXPLAIN:PostgreSQL generates a query plan for each query, because selecting the correct query path has a critical impact on performance. PostgreSQL itself contains a scheduler for optimal planning. We can use the EXPLAIN command to view the scheduler's query plan generated for each query.The query plan generated by PostgreSQL is a planning tree consisting

In a (bad) PostgreSQL query, just a little to change (any (array[...)) to any (VALUES (...)) will be able to reduce the query time from 20s to 0.2s. From the simplest learning to use EXPLAIN analyze, to learn to use the Postgres community a lot of learning time input will have a hundredfold time to return. Using Postgres to monitor slow Postgres queries Earlier this week, a primary key query for the small table (10gb,1500) on our graphics editor had

PostgreSQL CPU Full (100%) performance analysis and optimizationTransferred from: https://help.aliyun.com/knowledge_detail/43562.htmlIn database operations, a DBA often encounters a more urgent problem, that is, the sudden CPU full (CPU utilization reaches 100%), causing the business to stall. When the CPU is full, it is often necessary to start from the backend database, go back to the specific SQL, and fi

This is a test that was done a long time ago, recently in the collation of the PostgreSQL data related to the test, so also took it out to share with you.First explain the so-called PostgreSQL space performance, mainly based on the postgis of spatial data import performance, detailed PostGIS knowledge please Baidu, the

not specified in MongoDB and the MD5 value of 1–100,000,000 is treated as a normal field insert;c) in MySQL with 1–100,000,000 MD5 value of primary KEY, the data is inserted;d) primary KEY is not specifiedin MySQL and the MD5 value of 1–100,000,000 is considered a normal field insert.4. Analyze the insertion performance of MySQL and MongoDB based on the generate

Chapter III index operations and performance testing The importance of indexes under big data is not much to say.The following test used a MongoDB client tool Robomongo, you can choose to download on the Internet. Inserting test dataInsert 1 million test data first for (var i=1;i1000000; i++) { var person={name: "Jack" +i,age:i,address:["Henan", "Wuhan"],course:[{name: "Shuxue", Score:i },{Name: "Wu

for a standalone Pgsql server, such as 4G of memory, can be set to 3.5G (437500)Maintence_work_mem: The memory defined here is only used when create INDEX, vacuum, etc., so the frequency is not high, but often these instructions consume more resources, so the instructions should be quickly executed as soon as possible: to MAINTENCE_WORK_MEM large memory, such as 512M ( 524288)max_connections: Typically, the purpose of max_connections is to prevent max_connections * work_mem from exceeding the a

the maximum cache that PostgreSQL can use, and this number should be large enough for a standalone Pgsql server, such as 4G of memory, which can be set to 3.5G (437500)MAINTENCE_WORK_MEM: The memory defined here is only used when create INDEX, vacuum, etc., so the frequency used is not high, but often these instructions consume more resources, so the instructions should be quickly executed as soon as possible: to Maintence_ Work_mem large memory, suc

Tags: Plpgsql associate an ace off index function preFirst, the problem descriptionWhen the number of records for a table in PostgreSQL recently increased from million to 1 million (design capability is 100 million), the query performance of a multi-table associated view built on top of the table was dramatically slower (from about 10ms to 100s). After analyzing the query plan, it is found that the bottlene

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 results of large data

Tags: 2.4 cer first network password definition capability parameter securityMongoDB's library-level lock MongoDB is currently the most popular NoSQL database, with its natural document-type data structures, flexible data patterns, and easy-to-use horizontal scaling capabilities that have been favored by many developers. But gold is no can't pure perfect, MongoDB is not without its weaknesses, such as its l

Tags: Lucene style blog Color http intHubbledotnet starting from 1.2.3 version in the official code to support and MongoDB docking, MongoDB is a 10gen company developed No-sql database, its read and write performance than traditional relational database is much faster, and can be very convenient distributed deployment. Hubbledotnet also provides No-sql solutions

Tang Folin Lucene: http://blog.fulin.org/category/luceneAli Data team: http://www.alidata.orgFirst Lucene: http://www.cnblogs.com/forfuture1978/De Shenjun MONGODB:HTTP://WWW.CNBLOGS.COM/DAIZHJWang Xiaohua Algorithm series :http://blog.csdn.net/orbit/article/category/830251that blue-Sky PostgreSQL series:http://blog.163.com/li_hx/blog/#m =0t=3c=postgresqlDeep understanding of the PostgreSQL

PostgreSQL supports hstore to store data such as Key->value, which is similar to the array or JSON type. Efficient indexing is essential to the efficient use of this type of data. Let's take a look at the performance issues of two different types of indexes for the same retrieval request today.If we have such an original table, there is a Btree index based on the Str1 field.t_girl=# \d Status_check;