UnQLite is a in-process software library which implements a self-contained, serverless, zero-configuration, transactional NoSQL database engine. UnQLite is a document store database similar to MongoDB, Redis, CouchDB etc. as well a standard Key/Value store similar to BerkeleyDB, LevelDB, etc.
UnQLite is an embedded NoSQL (Key/Value store and Document-store) database engine. Unlike most other NoSQL databases, UnQLite does not have a separate server process. UnQLite reads and writes directly to ordinary disk files. A complete database with multiple collections, is contained in a single disk file. The database file format is cross-platform, you can freely copy a database between 32-bit and 64-bit systems or between big-endian and little-endian architectures. UnQLite features includes:
Column-store features
When your database grows into millions of records spread over lots of tables and used in business or science data warehouse applications, you really want a column-store database management system.
MonetDB innovates at all layers of a DBMS, e.g. a storage model based on vertical fragmentation, a modern CPU-tuned query execution architecture, automatic and self-tuning indexes, run-time query optimization, and a modular software architecture.
An easy-to-use secure configuration generator for web, database, and mail software
JavaScript SQL database for browser and Node.js.
Handles both traditional relational tables and nested JSON data (NoSQL).
Export, store, and import data from localStorage, IndexedDB, or Excel.
ConnectionStrings.com helps developers connect software to data. It's a straight to the point reference about connection strings, a knowledge base of articles and database connectivity content and a host of Q & A forums where developers help each other in finding solutions. »
SQL::Translator
is a group of Perl modules that manipulate structured data definitions (mostly database schemas) in interesting ways, such as converting among different dialects of CREATE
syntax (e.g., MySQL-to-Oracle), visualizations of schemas (pseudo-ER diagrams: GraphViz
or GD
), automatic code generation (using Class::DBI
), converting non-RDBMS files to SQL schemas (xSV text files, Excel spreadsheets), serializing parsed schemas (via Storable, YAML and XML), creating documentation (HTML and POD), and more. New to version 0.03 is the ability to talk directly to a database through DBI
to query for the structures of several databases.
Through the separation of the code into parsers and producers with an object model in between, it's possible to combine any parser with any producer, to plug in custom parsers or producers, or to manipulate the parsed data via the built-in object model. Presently only the definition parts of SQL are handled (CREATE
, ALTER)
, not the manipulation of data (INSERT
, UPDATE
, DELETE
).
Infer a probabilistic schema for a MongoDB collection.
Usage
mongodb-schema
can be used as a command line tool or programmatically in your application as a node module.
mongodb-schema mongodb://localhost:27017 db.collection
$ mongodump -d some_database -c some_collection
$ mongorestore -d some_other_db -c some_or_other_collection dump/some_collection.bson
You can select the collection via:
mongodump -d some_database -c some_collection
[Optionally, zip the dump (zip some_database.zip some_database/* -r
) and scp
it elsewhere]
Then restore it:
mongorestore -d some_other_db -c some_or_other_collection dump/some_collection.bson
Existing data in some_or_other_collection
will be preserved. That way you can "append" a collection from one database to another.
Prior to version 2.4.3, you will also need to add back your indexes after you copy over your data. Starting with 2.4.3, this process is automatic, and you can disable it with --noIndexRestore
.
MongoBooster is a shell-centric cross-platform GUI tool for MongoDB v2.4-3.4, which provides fluent query builder, SQL query SQL Query, update-in-place, ES2017 syntax support and true intellisense experience.
The GUI for MongoDB. Visually explore your data. Run ad hoc queries in seconds. Interact with your data with full CRUD functionality. View and optimize your query performance. Available on Linux, Mac, or Windows. Compass empowers you to make smarter decisions about indexing, document validation, and more.
This is a complete and feature rich Redis client for node.js. It supports all Redis commands and focuses on high performance.
Install with:
npm install redis
As with everything that contains valuable data, PostgreSQL databases should be backed up regularly. While the procedure is essentially simple, it is important to have a basic understanding of the underlying techniques and assumptions.
Unless you are a MySQL performance tuning expert, it can be enormously challenging and somewhat overwhelming to locate and eliminate MySQL bottlenecks. While many DBAs focus on improving the performance of the queries themselves, this post will focus on the highest-impact non-query items: MySQL Server Performance and OS Performance for MySQL.
Most options can be set using their actual names in the my.cnf.