DBMS > Bangdb vs. EJDB vs. HarperDB vs. Lovefield vs. Yaacomo

System Properties Comparison Bangdb vs. EJDB vs. HarperDB vs. Lovefield vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

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.

Embeddable relational database for web apps written in pure JavaScript

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store
Graph DBMS
Time Series DBMS

Document store

Relational DBMS

Secondary database models

Spatial DBMS

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

Score	0.08
Rank	#347	Overall
	#47	Document stores
	#34	Graph DBMS
	#31	Time Series DBMS

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	0.29
Rank	#293	Overall
	#133	Relational DBMS

Website

bangdb.com

github.com/Softmotions/ejdb

www.harperdb.io

google.github.io/lovefield

yaacomo.com

Technical documentation

docs.bangdb.com

github.com/Softmotions/ejdb/blob/master/README.md

docs.harperdb.io/docs

github.com/google/lovefield/blob/master/docs/spec_index.md

Developer

Sachin Sinha, BangDB

Softmotions

HarperDB

Google

Q2WEB GmbH

Initial release

2012

2017

2014

2009

Current release

BangDB 2.0, October 2021

3.1, August 2021

2.1.12, February 2017

License

Commercial or Open Source

Open Source

BSD 3

Open Source

GPLv2

commercial

free community edition available

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, C++

Node.js

JavaScript

Server operating systems

Linux

server-less

Linux
OS X

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

tested with Chrome, Firefox, IE, Safari

Android
Linux
Windows

Data scheme

schema-free

dynamic schema

yes

Typing

predefined data types such as float or date

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

yes

string, integer, double, bool, date, object_id

yes

JSON data types

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.

Secondary indexes

yes

secondary, composite, nested, reverse, geospatial

yes

SQL

Support of SQL

SQL like support with command line tool

SQL-like data manipulation statements

SQL-like query language

via JavaScript builder pattern

yes

APIs and other access methods

Proprietary protocol
RESTful HTTP API

in-process shared library

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

JDBC
ODBC

Supported programming languages

C
C#
C++
Java
Python

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

.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

JavaScript

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

Triggers

yes, Notifications (with Streaming only)

Using read-only observers

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

none

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

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

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

none

yes

the nodes on which a table resides can be defined

none

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Tunable consistency, set CAP knob accordingly

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes, optimistic concurrency control

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes, implements WAL (Write ahead log) as well

yes

yes, using LMDB

yes, by using IndexedDB or the cloud service Firebase Realtime Database

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

using MemoryDB

yes

User concepts

Access control

yes (enterprise version only)

Access rights for users and roles

fine grained access rights according to SQL-standard

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More resources

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