DBMS > EJDB vs. Memcached vs. OpenTSDB vs. SwayDB vs. WakandaDB

System Properties Comparison EJDB vs. Memcached vs. OpenTSDB vs. SwayDB vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

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

In-memory key-value store, originally intended for caching

Scalable Time Series DBMS based on HBase

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	19.42
Rank	#32	Overall
	#4	Key-value stores

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

github.com/Softmotions/ejdb

Technical documentation

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

github.com/memcached/memcached/wiki

opentsdb.net/docs/build/html/index.html

wakanda.github.io/doc

Developer

Softmotions

Danga Interactive

originally developed by Brad Fitzpatrick for LiveJournal

currently maintained by Yahoo and other contributors

Simer Plaha

Wakanda SAS

Initial release

2012

2003

2011

2018

2012

Current release

1.6.25, March 2024

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

Open Source

GPLv2

Open Source

BSD license

Open Source

LGPL

Open Source

GNU Affero GPL V3.0

Open Source

AGPLv3, extended commercial license available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Scala

C++, JavaScript

Server operating systems

server-less

FreeBSD
Linux
OS X
Unix
Windows

Linux
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

numeric data for metrics, strings for tags

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

SQL

Support of SQL

APIs and other access methods

in-process shared library

Proprietary protocol

HTTP API
Telnet API

RESTful HTTP API

Supported programming languages

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

.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby

Erlang
Go
Java
Python
R
Ruby

Java
Kotlin
Scala

JavaScript

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on HBase

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Repcached, a Memcached patch, provides this functionallity

selectable replication factor

based on HBase

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Immediate Consistency

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

Atomic execution of operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

User concepts

Access control

yes

using SASL (Simple Authentication and Security Layer) protocol

yes

More information provided by the system vendor

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More resources

DB-Engines blog posts

Redis extends the lead in the DB-Engines key-value store ranking
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Time Series DBMS are the database category with the fastest increase in popularity
4 July 2016, Matthias Gelbmann

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