cassandra mongodb comparison

Comparison between MongoDB and MySQL commands Traditional relational databases are generally composed of three levels: database, table, and record. MongoDB is composedDatabase, collection, and document)Three layers. MongoDB has no concept of columns, rows, and links for tables in relational databases, which reflects th

(*) FROM user WHERE 'name' = 'starlil'Mongo:Db. user. find ({'name': 'starlil'}). count () MySQL:SELECT * FROM user limit 10, 20Mongo:Db. user. find (). skip (10). limit (20) MySQL:SELECT * FROM user WHERE 'age' IN (25, 35, 45)Mongo:Db. user. find ({'age': {$ in: [25, 35, 45]}) MySQL:SELECT * FROM user order by age DESCMongo:Db. user. find (). sort ({'age':-1 }) MySQL:Select distinct (name) FROM user WHERE age> 20Mongo:Db. user. distinct ('name', {'age': {$ lt: 20 }}) MySQL:SELECT name, sum (ma

copy set of a hybrid engine. In the replication set, you can configure Wiredtiger to accept a large amount of write data load, and then use another node to configure the Mmap engine to be used by some read data services, to replicate the data between the Assembly automatic main library and other libraries, their underlying storage engine is independent.If your data files are created using the Mmap engine, you will need to create a new database, and if you need to run with a Wiredtirger node, he

From:http://yang.u85.us/memcache_redis_mongodb.pdf A comparison of Redis, Memcache, and MongoDB is made from the following dimensions.1. Performanceare relatively high, performance should not be a bottleneck for us.In general, TPS is about the same as Redis and Memcache, more than MongoDB.2, the convenience of the operationMemcache data structure is single. (Key

From the following several dimensions, the Redis, Memcache, MongoDB made a comparison, welcome to shoot Bricks1. Performanceare relatively high, performance is not a bottleneck for usIn general, the TPS is about the same as Redis and Memcache, more than MongoDB2, the convenience of the operationMemcache Data Structure SingleRedis is rich, data manipulation, Redis better, less network IO timesMongoDB support

SELECT * from the users ORDER by name Db.users.find (). Sort ({name:-1}) Sort SELECT * from Users ORDER by name DESC Db.users.find (). Sort ({name:-1}) Sort EXPLAIN SELECT * from Users where z=3 Db.users.find ({Z:3}). Explain () Get Storage Path Update users set a=1 where b= ' Q ' Db.users.update ({b: ' Q '}, {$set: {a:1}}, False, True) Update record Update users set a=a+2 where b= ' Q

improved.B. MongoV2.6.4 as the lock conflict changes, its read-Write throughput trends:Scenario: This was tested on my own development machine, with 10 concurrent read and write threads tested, and the horizontal axis represented: The ratio of locks (time of lock wait/read/write Transaction completion)Results: The results show that the overall throughput decreases with the increase of lock waiting ratio.C. MongoV2.6.4 test the performance comparison

modification because of the isolation bounds of the serial transaction. MONGO has no multi-statement transaction syntax. Another single update involves multiple documents and non-atomic execution. When find involves multiple documents, the readConcern进行并发修改隔离。 bulk syntax may be partially successful by not supporting multi-table multi-row transactions that are common in MySQL, or single-table multi-line transactions, and can only use compensation mechanisms to achieve eventual consistency.

WiredtigerMongoDB itself owns the MMAPv1 engine, and in version 3.0 It added the previously acquired Wiredtiger storage engine technology.through Wiredtiger , MongoDB 3.0 implements the Document-level concurrency control (Concurrency Control), thus greatly improving the write load under large concurrency . Users can choose the compression ratio of their own storage data, MongoDB 3.0 provides the maximum com

MongoDB and MySQL operation comparison table and the difference introduction MySQL and MongoDB are common open source databases, but MySQL is a traditional relational database, MongoDB is a non-relational database, also known as a document database, is a NoSQL database. They each have their own merits, the key

I searched an article todayArticleNosql solution: Evaluation and comparison: MongoDB vs redis, Tokyo cabinet, and Berkeley dB. It is a Chinese translation version, which is well written by the author, but it takes several hours to insert 0.2 billion data records. I am more confident about this. I just wrote a database prototype in the last month. Currently, I am on a 1 GB memory VM on my laptop, insert 0.2

Label:MongoDB Grammar MySQL syntax Db.test.find ({' name ': ' Foobar '}) Db.test.find () Db.test.find ({' ID ': ten}). Count () Db.test.find (). Skip () Limit Db.test.find ({' ID ': {$in: [25,35,45]}} Db.test.find (). Sort ({' ID ': -1}) Db.test.distinct (' name ', {' ID ': {$lt:}}) Db.test.group ({key:{' name ': ' true},cond:{' name ': ' foo '},reduce:function (obj,prev) {prev.msum+=obj.marks;},initial: {msum:0}}) Db.test.find (' this.id Db.test.insert ({' name ': ' Foobar ', ' age '

First, the question The amount of data per query is enormous and requires the server to respond to user requests more quickly. Second, the solution 1. Cache database data via the high-speed server cache 2. In-Memory database Third, mainstream cache and database comparison Common relational database MySQL In-Memory database Redis NoSQL Database MongoDB Memory Cache memcached

Mongodb:It's an in-memory database, and the data is in memory.The operation of the data is mostly in memory, but MongoDB is not a pure memory database.Persistence mode:All of MongoDB's data is actually stored on the hard disk, and all the data to be manipulated is mapped to an area of memory in a mmap way.MongoDB then modifies the data in this area to avoid fragmented hard disk operations.As for the contents of mmap flush to the hard disk is the opera

}}). Count () Create index Myindexname on users (name) Db.users.ensureIndex ({name:1}) Create index Myindexname on users (name,ts desc) Db.users.ensureIndex ({name:1,ts:-1}) Explain select * from users where z=3 Db.users.find ({Z:3}). Explain () Update users set a=1 where b= ' Q ' Db.users.update ({b: ' Q '}, {$set: {a:1}}, False, True)

Both MongoDB and Redis are NoSQL, using structured data storage. There are some differences between the two in the usage scene, which is mainly due to the process of the memory mapping, and the persistence processing method is different.MongoDB recommended cluster deployment, more considering the cluster scenario, Redis is more emphasis on process sequential write, although the support cluster, but also limited to the master-slave mode.

Both MongoDB and Redis are NoSQL, using structured data storage. There are some differences between the two in the usage scene, which is mainly due to the process of the memory mapping, and the persistence processing method is different.MongoDB recommended cluster deployment, more considering the cluster scenario, Redis is more emphasis on process sequential write, although the support cluster, but also limited to the master-slave mode.

From:http://yang.u85.us/memcache_redis_mongodb.pdfA comparison of Redis, Memcache, and MongoDB is made from the following dimensions.1. Performanceare relatively high, performance should not be a bottleneck for us.In general, TPS is about the same as Redis and Memcache, more than MongoDB.2, the convenience of the operationMemcache data structure is single. (Key-v

Db.users.find (). Sort ({name:-1}) Sort SELECT * from Users ORDER by name DESC Db.users.find (). Sort ({name:-1}) Sort EXPLAIN SELECT * from Users where z=3 Db.users.find ({Z:3}). Explain () Get Storage Path Update users set a=1 where b= ' Q ' Db.users.update ({b: ' Q '}, {$set: {a:1}}, False, True) Update record Update users set a=a+2 where b= ' Q ' Db.users.update ({b: ' Q '}, {$inc: {a:2}}, F

into JSON, but some data update inconvenient)2) The team develops familiar technologies, such as a team that has been using MC for a limited selection of MC rather than Redis.In the middle of a serious situation, the development team has been using MOGODB to continue to select Mogodb in a scenario suitable for KV nosq.A book recommended to you: Memcache and Redis are key-value storage systems, whereas Redis may be more adaptable than memcache, storing more value types, and Redis supports master