The JavaScript Database
Embedded persistent or in memory database for Node.js, nw.js, Electron and browsers, 100% JavaScript, no binary dependency. API is a subset of MongoDB's and it's plenty fast.
IMPORTANT NOTE: Please don't submit issues for questions regarding your code. Only actual bugs or feature requests will be answered, all others will be closed without comment. Also, please follow the bug reporting guidelines and check the change log before submitting an already fixed bug :)
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Installation, tests
Module name on npm and bower is nedb
.
npm install nedb --save # Put latest version in your package.json
npm test # You'll need the dev dependencies to launch tests
bower install nedb # For the browser versions, which will be in browser-version/out
API
It is a subset of MongoDB's API (the most used operations).
- Creating/loading a database
- Persistence
- Inserting documents
- Finding documents
- Counting documents
- Updating documents
- Removing documents
- Indexing
- Browser version
Creating/loading a database
You can use NeDB as an in-memory only datastore or as a persistent datastore. One datastore is the equivalent of a MongoDB collection. The constructor is used as follows new Datastore(options)
where options
is an object with the following fields:
filename
(optional): path to the file where the data is persisted. If left blank, the datastore is automatically considered in-memory only. It cannot end with a~
which is used in the temporary files NeDB uses to perform crash-safe writes.inMemoryOnly
(optional, defaults tofalse
): as the name implies.timestampData
(optional, defaults tofalse
): timestamp the insertion and last update of all documents, with the fieldscreatedAt
andupdatedAt
. User-specified values override automatic generation, usually useful for testing.autoload
(optional, defaults tofalse
): if used, the database will automatically be loaded from the datafile upon creation (you don't need to callloadDatabase
). Any command issued before load is finished is buffered and will be executed when load is done.onload
(optional): if you use autoloading, this is the handler called after theloadDatabase
. It takes oneerror
argument. If you use autoloading without specifying this handler, and an error happens during load, an error will be thrown.afterSerialization
(optional): hook you can use to transform data after it was serialized and before it is written to disk. Can be used for example to encrypt data before writing database to disk. This function takes a string as parameter (one line of an NeDB data file) and outputs the transformed string, which must absolutely not contain a\n
character (or data will be lost).beforeDeserialization
(optional): inverse ofafterSerialization
. Make sure to include both and not just one or you risk data loss. For the same reason, make sure both functions are inverses of one another. Some failsafe mechanisms are in place to prevent data loss if you misuse the serialization hooks: NeDB checks that never one is declared without the other, and checks that they are reverse of one another by testing on random strings of various lengths. In addition, if too much data is detected as corrupt, NeDB will refuse to start as it could mean you're not using the deserialization hook corresponding to the serialization hook used before (see below).corruptAlertThreshold
(optional): between 0 and 1, defaults to 10%. NeDB will refuse to start if more than this percentage of the datafile is corrupt. 0 means you don't tolerate any corruption, 1 means you don't care.compareStrings
(optional): function compareStrings(a, b) compares strings a and b and return -1, 0 or 1. If specified, it overrides default string comparison which is not well adapted to non-US characters in particular accented letters. NativelocalCompare
will most of the time be the right choicenodeWebkitAppName
(optional, DEPRECATED): if you are using NeDB from whithin a Node Webkit app, specify its name (the same one you use in thepackage.json
) in this field and thefilename
will be relative to the directory Node Webkit uses to store the rest of the application's data (local storage etc.). It works on Linux, OS X and Windows. Now that you can userequire('nw.gui').App.dataPath
in Node Webkit to get the path to the data directory for your application, you should not use this option anymore and it will be removed.
If you use a persistent datastore without the autoload
option, you need to call loadDatabase
manually.
This function fetches the data from datafile and prepares the database. Don't forget it! If you use a
persistent datastore, no command (insert, find, update, remove) will be executed before loadDatabase
is called, so make sure to call it yourself or use the autoload
option.
Also, if loadDatabase
fails, all commands registered to the executor afterwards will not be executed. They will be registered and executed, in sequence, only after a successful loadDatabase
.
// Type 1: In-memory only datastore (no need to load the database)var Datastore = db = ; // Type 2: Persistent datastore with manual loadingvar Datastore = db = filename: 'path/to/datafile' ;db; // Type 3: Persistent datastore with automatic loadingvar Datastore = db = filename: 'path/to/datafile' autoload: true ;// You can issue commands right away // Type 4: Persistent datastore for a Node Webkit app called 'nwtest'// For example on Linux, the datafile will be ~/.config/nwtest/nedb-data/something.dbvar Datastore = path = db = filename: path ; // Of course you can create multiple datastores if you need several// collections. In this case it's usually a good idea to use autoload for all collections.db = {};dbusers = 'path/to/users.db';dbrobots = 'path/to/robots.db'; // You need to load each database (here we do it asynchronously)dbusers;dbrobots;
Persistence
Under the hood, NeDB's persistence uses an append-only format, meaning that all updates and deletes actually result in lines added at the end of the datafile, for performance reasons. The database is automatically compacted (i.e. put back in the one-line-per-document format) every time you load each database within your application.
You can manually call the compaction function with yourDatabase.persistence.compactDatafile
which takes no argument. It queues a compaction of the datafile in the executor, to be executed sequentially after all pending operations. The datastore will fire a compaction.done
event once compaction is finished.
You can also set automatic compaction at regular intervals with yourDatabase.persistence.setAutocompactionInterval(interval)
, interval
in milliseconds (a minimum of 5s is enforced), and stop automatic compaction with yourDatabase.persistence.stopAutocompaction()
.
Keep in mind that compaction takes a bit of time (not too much: 130ms for 50k records on a typical development machine) and no other operation can happen when it does, so most projects actually don't need to use it.
Compaction will also immediately remove any documents whose data line has become corrupted, assuming that the total percentage of all corrupted documents in that database still falls below the specified corruptAlertThreshold
option's value.
Durability works similarly to major databases: compaction forces the OS to physically flush data to disk, while appends to the data file do not (the OS is responsible for flushing the data). That guarantees that a server crash can never cause complete data loss, while preserving performance. The worst that can happen is a crash between two syncs, causing a loss of all data between the two syncs. Usually syncs are 30 seconds appart so that's at most 30 seconds of data. This post by Antirez on Redis persistence explains this in more details, NeDB being very close to Redis AOF persistence with appendfsync
option set to no
.
Inserting documents
The native types are String
, Number
, Boolean
, Date
and null
. You can also use
arrays and subdocuments (objects). If a field is undefined
, it will not be saved (this is different from
MongoDB which transforms undefined
in null
, something I find counter-intuitive).
If the document does not contain an _id
field, NeDB will automatically generated one for you (a 16-characters alphanumerical string). The _id
of a document, once set, cannot be modified.
Field names cannot begin by '$' or contain a '.'.
var doc = hello: 'world' n: 5 today: nedbIsAwesome: true notthere: null notToBeSaved: undefined // Will not be saved fruits: 'apple' 'orange' 'pear' infos: name: 'nedb' ; db;
You can also bulk-insert an array of documents. This operation is atomic, meaning that if one insert fails due to a unique constraint being violated, all changes are rolled back.
db; // If there is a unique constraint on field 'a', this will faildb;
Finding documents
Use find
to look for multiple documents matching you query, or findOne
to look for one specific document. You can select documents based on field equality or use comparison operators ($lt
, $lte
, $gt
, $gte
, $in
, $nin
, $ne
). You can also use logical operators $or
, $and
, $not
and $where
. See below for the syntax.
You can use regular expressions in two ways: in basic querying in place of a string, or with the $regex
operator.
You can sort and paginate results using the cursor API (see below).
You can use standard projections to restrict the fields to appear in the results (see below).
Basic querying
Basic querying means are looking for documents whose fields match the ones you specify. You can use regular expression to match strings. You can use the dot notation to navigate inside nested documents, arrays, arrays of subdocuments and to match a specific element of an array.
// Let's say our datastore contains the following collection// { _id: 'id1', planet: 'Mars', system: 'solar', inhabited: false, satellites: ['Phobos', 'Deimos'] }// { _id: 'id2', planet: 'Earth', system: 'solar', inhabited: true, humans: { genders: 2, eyes: true } }// { _id: 'id3', planet: 'Jupiter', system: 'solar', inhabited: false }// { _id: 'id4', planet: 'Omicron Persei 8', system: 'futurama', inhabited: true, humans: { genders: 7 } }// { _id: 'id5', completeData: { planets: [ { name: 'Earth', number: 3 }, { name: 'Mars', number: 2 }, { name: 'Pluton', number: 9 } ] } } // Finding all planets in the solar systemdb; // Finding all planets whose name contain the substring 'ar' using a regular expressiondb; // Finding all inhabited planets in the solar systemdb; // Use the dot-notation to match fields in subdocumentsdb; // Use the dot-notation to navigate arrays of subdocumentsdb; db; db; // You can also deep-compare objects. Don't confuse this with dot-notation!db; // Find all documents in the collectiondb; // The same rules apply when you want to only find one documentdb;
Operators ($lt, $lte, $gt, $gte, $in, $nin, $ne, $exists, $regex)
The syntax is { field: { $op: value } }
where $op
is any comparison operator:
$lt
,$lte
: less than, less than or equal$gt
,$gte
: greater than, greater than or equal$in
: member of.value
must be an array of values$ne
,$nin
: not equal, not a member of$exists
: checks whether the document posses the propertyfield
.value
should be true or false$regex
: checks whether a string is matched by the regular expression. Contrary to MongoDB, the use of$options
with$regex
is not supported, because it doesn't give you more power than regex flags. Basic queries are more readable so only use the$regex
operator when you need to use another operator with it (see example below)
// $lt, $lte, $gt and $gte work on numbers and stringsdb; // When used with strings, lexicographical order is useddb // Using $in. $nin is used in the same waydb; // Using $existsdb; // Using $regex with another operatordb;
Array fields
When a field in a document is an array, NeDB first tries to see if the query value is an array to perform an exact match, then whether there is an array-specific comparison function (for now there is only $size
and $elemMatch
) being used. If not, the query is treated as a query on every element and there is a match if at least one element matches.
$size
: match on the size of the array$elemMatch
: matches if at least one array element matches the query entirely
// Exact matchdbdb // Using an array-specific comparison function// $elemMatch operator will provide match for a document, if an element from the array field satisfies all the conditions specified with the `$elemMatch` operatordb; db; // You can use inside #elemMatch query any known document query operatordb; // Note: you can't use nested comparison functions, e.g. { $size: { $lt: 5 } } will throw an errordb; db; // If a document's field is an array, matching it means matching any element of the arraydb; // This also works for queries that use comparison operatorsdb; // This also works with the $in and $nin operatordb;
Logical operators $or, $and, $not, $where
You can combine queries using logical operators:
- For
$or
and$and
, the syntax is{ $op: [query1, query2, ...] }
. - For
$not
, the syntax is{ $not: query }
- For
$where
, the syntax is{ $where: function () { /* object is "this", return a boolean */ } }
db; db; db; // You can mix normal queries, comparison queries and logical operatorsdb;
Sorting and paginating
If you don't specify a callback to find
, findOne
or count
, a Cursor
object is returned. You can modify the cursor with sort
, skip
and limit
and then execute it with exec(callback)
.
// Let's say the database contains these 4 documents// doc1 = { _id: 'id1', planet: 'Mars', system: 'solar', inhabited: false, satellites: ['Phobos', 'Deimos'] }// doc2 = { _id: 'id2', planet: 'Earth', system: 'solar', inhabited: true, humans: { genders: 2, eyes: true } }// doc3 = { _id: 'id3', planet: 'Jupiter', system: 'solar', inhabited: false }// doc4 = { _id: 'id4', planet: 'Omicron Persei 8', system: 'futurama', inhabited: true, humans: { genders: 7 } } // No query used means all results are returned (before the Cursor modifiers)db; // You can sort in reverse order like thisdb; // You can sort on one field, then another, and so on like this:db ... // You understand how this works!
Projections
You can give find
and findOne
an optional second argument, projections
. The syntax is the same as MongoDB: { a: 1, b: 1 }
to return only the a
and b
fields, { a: 0, b: 0 }
to omit these two fields. You cannot use both modes at the time, except for _id
which is by default always returned and which you can choose to omit. You can project on nested documents.
// Same database as above // Keeping only the given fieldsdb; // Keeping only the given fields but removing _iddb; // Omitting only the given fields and removing _iddb; // Failure: using both modes at the same timedb; // You can also use it in a Cursor way but this syntax is not compatible with MongoDBdb; // Project on a nested documentdb;
Counting documents
You can use count
to count documents. It has the same syntax as find
. For example:
// Count all planets in the solar systemdb; // Count all documents in the datastoredb;
Updating documents
db.update(query, update, options, callback)
will update all documents matching query
according to the update
rules:
query
is the same kind of finding query you use withfind
andfindOne
update
specifies how the documents should be modified. It is either a new document or a set of modifiers (you cannot use both together, it doesn't make sense!)- A new document will replace the matched docs
- The modifiers create the fields they need to modify if they don't exist, and you can apply them to subdocs. Available field modifiers are
$set
to change a field's value,$unset
to delete a field,$inc
to increment a field's value and$min
/$max
to change field's value, only if provided value is less/greater than current value. To work on arrays, you have$push
,$pop
,$addToSet
,$pull
, and the special$each
and$slice
. See examples below for the syntax.
options
is an object with two possible parametersmulti
(defaults tofalse
) which allows the modification of several documents if set to trueupsert
(defaults tofalse
) if you want to insert a new document corresponding to theupdate
rules if yourquery
doesn't match anything. If yourupdate
is a simple object with no modifiers, it is the inserted document. In the other case, thequery
is stripped from all operator recursively, and theupdate
is applied to it.returnUpdatedDocs
(defaults tofalse
, not MongoDB-compatible) if set to true and update is not an upsert, will return the array of documents matched bu the find query and updated. Updated documents will be returned even if the update did not actually modify them
callback
(optional) signature:(err, numAffected, affectedDocuments, upsert)
. Warning: the API was changed between v1.7.4 and v1.8. Please refer to the change log to see the change.- For an upsert,
affectedDocuments
contains the inserted document and theupsert
flag is set totrue
. - For a standard update with
returnUpdatedDocs
flag set tofalse
,affectedDocuments
is not set. - For a standard update with
returnUpdatedDocs
flag set totrue
andmulti
tofalse
,affectedDocuments
is the updated document. - For a standard update with
returnUpdatedDocs
flag set totrue
andmulti
totrue
,affectedDocuments
is the array of updated documents.
- For an upsert,
Note: you can't change a document's _id.
// Let's use the same example collection as in the "finding document" part// { _id: 'id1', planet: 'Mars', system: 'solar', inhabited: false }// { _id: 'id2', planet: 'Earth', system: 'solar', inhabited: true }// { _id: 'id3', planet: 'Jupiter', system: 'solar', inhabited: false }// { _id: 'id4', planet: 'Omicron Persia 8', system: 'futurama', inhabited: true } // Replace a document by anotherdb; // Set an existing field's valuedb; // Setting the value of a non-existing field in a subdocument by using the dot-notationdb; // Deleting a fielddb; // Upserting a documentdb; // If you upsert with a modifier, the upserted doc is the query modified by the modifier// This is simpler than it sounds :)db; // If we insert a new document { _id: 'id6', fruits: ['apple', 'orange', 'pear'] } in the collection,// let's see how we can modify the array field atomically // $push inserts new elements at the end of the arraydb; // $pop removes an element from the end (if used with 1) or the front (if used with -1) of the arraydb; // $addToSet adds an element to an array only if it isn't already in it// Equality is deep-checked (i.e. $addToSet will not insert an object in an array already containing the same object)// Note that it doesn't check whether the array contained duplicates before or notdb; // $pull removes all values matching a value or even any NeDB query from the arraydb;db; // $each can be used to $push or $addToSet multiple values at once// This example works the same way with $addToSetdb; // $slice can be used in cunjunction with $push and $each to limit the size of the resulting array.// A value of 0 will update the array to an empty array. A positive value n will keep only the n first elements// A negative value -n will keep only the last n elements.// If $slice is specified but not $each, $each is set to []db; // $min/$max to update only if provided value is less/greater than current value// Let's say the database contains this document// doc = { _id: 'id', name: 'Name', value: 5 }db; db;
Removing documents
db.remove(query, options, callback)
will remove all documents matching query
according to options
query
is the same as the ones used for finding and updatingoptions
only one option for now:multi
which allows the removal of multiple documents if set to true. Default is falsecallback
is optional, signature: err, numRemoved
// Let's use the same example collection as in the "finding document" part// { _id: 'id1', planet: 'Mars', system: 'solar', inhabited: false }// { _id: 'id2', planet: 'Earth', system: 'solar', inhabited: true }// { _id: 'id3', planet: 'Jupiter', system: 'solar', inhabited: false }// { _id: 'id4', planet: 'Omicron Persia 8', system: 'futurama', inhabited: true } // Remove one document from the collection// options set to {} since the default for multi is falsedb; // Remove multiple documentsdb; // Removing all documents with the 'match-all' querydb;
Indexing
NeDB supports indexing. It gives a very nice speed boost and can be used to enforce a unique constraint on a field. You can index any field, including fields in nested documents using the dot notation. For now, indexes are only used to speed up basic queries and queries using $in
, $lt
, $lte
, $gt
and $gte
. The indexed values cannot be of type array of object.
To create an index, use datastore.ensureIndex(options, cb)
, where callback is optional and get passed an error if any (usually a unique constraint that was violated). ensureIndex
can be called when you want, even after some data was inserted, though it's best to call it at application startup. The options are:
- fieldName (required): name of the field to index. Use the dot notation to index a field in a nested document.
- unique (optional, defaults to
false
): enforce field uniqueness. Note that a unique index will raise an error if you try to index two documents for which the field is not defined. - sparse (optional, defaults to
false
): don't index documents for which the field is not defined. Use this option along with "unique" if you want to accept multiple documents for which it is not defined. - expireAfterSeconds (number of seconds, optional): if set, the created index is a TTL (time to live) index, that will automatically remove documents when the system date becomes larger than the date on the indexed field plus
expireAfterSeconds
. Documents where the indexed field is not specified or not aDate
object are ignored
Note: the _id
is automatically indexed with a unique constraint, no need to call ensureIndex
on it.
You can remove a previously created index with datastore.removeIndex(fieldName, cb)
.
If your datastore is persistent, the indexes you created are persisted in the datafile, when you load the database a second time they are automatically created for you. No need to remove any ensureIndex
though, if it is called on a database that already has the index, nothing happens.
db; // Using a unique constraint with the indexdb; // Using a sparse unique indexdb; // Format of the error message when the unique constraint is not metdb; // Remove index on field somefielddb; // Example of using expireAfterSeconds to remove documents 1 hour// after their creation (db's timestampData option is true here)db; // You can also use the option to set an expiration date like sodb;
Note: the ensureIndex
function creates the index synchronously, so it's best to use it at application startup. It's quite fast so it doesn't increase startup time much (35 ms for a collection containing 10,000 documents).
Browser version
The browser version and its minified counterpart are in the browser-version/out
directory. You only need to require nedb.js
or nedb.min.js
in your HTML file and the global object Nedb
can be used right away, with the same API as the server version:
<script src="nedb.min.js"></script>
<script>
var db = new Nedb(); // Create an in-memory only datastore
db.insert({ planet: 'Earth' }, function (err) {
db.find({}, function (err, docs) {
// docs contains the two planets Earth and Mars
});
});
</script>
If you specify a filename
, the database will be persistent, and automatically select the best storage method available (IndexedDB, WebSQL or localStorage) depending on the browser. In most cases that means a lot of data can be stored, typically in hundreds of MB. WARNING: the storage system changed between v1.3 and v1.4 and is NOT back-compatible! Your application needs to resync client-side when you upgrade NeDB.
NeDB is compatible with all major browsers: Chrome, Safari, Firefox, IE9+. Tests are in the browser-version/test
directory (files index.html
and testPersistence.html
).
If you fork and modify nedb, you can build the browser version from the sources, the build script is browser-version/build.js
.
Performance
Speed
NeDB is not intended to be a replacement of large-scale databases such as MongoDB, and as such was not designed for speed. That said, it is still pretty fast on the expected datasets, especially if you use indexing. On a typical, not-so-fast dev machine, for a collection containing 10,000 documents, with indexing:
- Insert: 10,680 ops/s
- Find: 43,290 ops/s
- Update: 8,000 ops/s
- Remove: 11,750 ops/s
You can run these simple benchmarks by executing the scripts in the benchmarks
folder. Run them with the --help
flag to see how they work.
Memory footprint
A copy of the whole database is kept in memory. This is not much on the expected kind of datasets (20MB for 10,000 2KB documents).
Use in other services
- connect-nedb-session is a session store for Connect and Express, backed by nedb
- If you mostly use NeDB for logging purposes and don't want the memory footprint of your application to grow too large, you can use NeDB Logger to insert documents in a NeDB-readable database
- If you've outgrown NeDB, switching to MongoDB won't be too hard as it is the same API. Use this utility to transfer the data from a NeDB database to a MongoDB collection
- An ODM for NeDB: Camo
Pull requests
If you submit a pull request, thanks! There are a couple rules to follow though to make it manageable:
- The pull request should be atomic, i.e. contain only one feature. If it contains more, please submit multiple pull requests. Reviewing massive, 1000 loc+ pull requests is extremely hard.
- Likewise, if for one unique feature the pull request grows too large (more than 200 loc tests not included), please get in touch first.
- Please stick to the current coding style. It's important that the code uses a coherent style for readability.
- Do not include sylistic improvements ("housekeeping"). If you think one part deserves lots of housekeeping, use a separate pull request so as not to pollute the code.
- Don't forget tests for your new feature. Also don't forget to run the whole test suite before submitting to make sure you didn't introduce regressions.
- Do not build the browser version in your branch, I'll take care of it once the code is merged.
- Update the readme accordingly.
- Last but not least: keep in mind what NeDB's mindset is! The goal is not to be a replacement for MongoDB, but to have a pure JS database, easy to use, cross platform, fast and expressive enough for the target projects (small and self contained apps on server/desktop/browser/mobile). Sometimes it's better to shoot for simplicity than for API completeness with regards to MongoDB.
Bug reporting guidelines
If you report a bug, thank you! That said for the process to be manageable please strictly adhere to the following guidelines. I'll not be able to handle bug reports that don't:
- Your bug report should be a self-containing gist complete with a package.json for any dependencies you need. I need to run through a simple
git clone gist; npm install; node bugreport.js
, nothing more. - It should use assertions to showcase the expected vs actual behavior and be hysteresis-proof. It's quite simple in fact, see this example: https://gist.github.com/louischatriot/220cf6bd29c7de06a486
- Simplify as much as you can. Strip all your application-specific code. Most of the time you will see that there is no bug but an error in your code :)
- 50 lines max. If you need more, read the above point and rework your bug report. If you're really convinced you need more, please explain precisely in the issue.
Bitcoins
You don't have time? You can support NeDB by sending bitcoins to this address: 1dDZLnWpBbodPiN8sizzYrgaz5iahFyb1
License
See License