DBMS > Bangdb vs. HarperDB vs. KeyDB vs. LokiJS vs. Microsoft SQL Server

System Properties Comparison Bangdb vs. HarperDB vs. KeyDB vs. LokiJS vs. Microsoft SQL Server

Editorial information provided by DB-Engines

Name

Description

Converged and high performance database for device data, events, time series, document and graph

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

An ultra-fast, open source Key-value store fully compatible with Redis API, modules, and protocols

In-memory JavaScript DBMS

Microsofts flagship relational DBMS

Primary database model

Document store
Graph DBMS
Time Series DBMS

Secondary database models

Spatial DBMS

Document store
Graph DBMS
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.16
Rank	#338	Overall
	#47	Document stores
	#32	Graph DBMS
	#31	Time Series DBMS

Score	0.60
Rank	#244	Overall
	#38	Document stores

Score	0.70
Rank	#229	Overall
	#32	Key-value stores

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	821.56
Rank	#3	Overall
	#3	Relational DBMS

Website

bangdb.com

www.harperdb.io

github.com/Snapchat/KeyDB
keydb.dev

github.com/techfort/LokiJS

www.microsoft.com/en-us/sql-server

Technical documentation

docs.bangdb.com

docs.harperdb.io/docs

docs.keydb.dev

techfort.github.io/LokiJS

learn.microsoft.com/en-US/sql/sql-server

Developer

Sachin Sinha, BangDB

HarperDB

EQ Alpha Technology Ltd.

Microsoft

Initial release

2012

2017

2019

2014

1989

Current release

BangDB 2.0, October 2021

3.1, August 2021

SQL Server 2022, November 2022

License

Commercial or Open Source

Open Source

BSD 3

commercial

free community edition available

Open Source

BSD-3

Open Source

commercial

restricted free version is available

Cloud-based only

Only available as a cloud service

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Implementation language

C, C++

Node.js

C++

JavaScript

C++

Server operating systems

Linux

Linux
OS X

Linux

server-less, requires a JavaScript environment (browser, Node.js)

Linux
Windows

Data scheme

schema-free

dynamic schema

schema-free

yes

Typing

predefined data types such as float or date

yes: string, long, double, int, geospatial, stream, events

yes

JSON data types

partial

Supported data types are strings, hashes, lists, sets and sorted sets, bit arrays, hyperloglogs and geospatial indexes

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

by using the Redis Search module

yes

via views

yes

SQL

Support of SQL

SQL like support with command line tool

SQL-like data manipulation statements

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Proprietary protocol

RESP - REdis Serialization Protoco

JavaScript API

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

Supported programming languages

C
C#
C++
Java
Python

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

C
C#
C++
Clojure
Crystal
D
Dart
Elixir
Erlang
Fancy
Go
Haskell
Haxe
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Objective-C
OCaml
Pascal
Perl
PHP
Prolog
Pure Data
Python
R
Rebol
Ruby
Rust
Scala
Scheme
Smalltalk
Swift
Tcl
Visual Basic

JavaScript

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

Lua

View functions in JavaScript

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

Triggers

yes, Notifications (with Streaming only)

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding (enterprise version only). P2P based virtual network overlay with consistent hashing and chord algorithm

A table resides as a whole on one (or more) nodes in a cluster

Sharding

none

tables can be distributed across several files (horizontal partitioning); sharding through federation

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor, Knob for CAP (enterprise version only)

yes

the nodes on which a table resides can be defined

Multi-source replication
Source-replica replication

none

yes, but depending on the SQL-Server Edition

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Eventual Consistency
Strong eventual consistency with CRDTs

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Atomic execution of specific operations

Optimistic locking, atomic execution of commands blocks and scripts

atomic operations within a single collection possible

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes, using LMDB

yes

Configurable mechanisms for persistency via snapshots and/or operations logs

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes, run db with in-memory only mode

yes

User concepts

Access control

yes (enterprise version only)

Access rights for users and roles

simple password-based access control and ACL

fine grained access rights according to SQL-standard

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