DBMS > EJDB vs. etcd vs. OpenTSDB vs. SQLite vs. TimescaleDB

System Properties Comparison EJDB vs. etcd vs. OpenTSDB vs. SQLite vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

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

A distributed reliable key-value store

Scalable Time Series DBMS based on HBase

Widely used embeddable, in-process RDBMS

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Secondary database models

Relational DBMS

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

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	7.03
Rank	#54	Overall
	#5	Key-value stores

Score	1.68
Rank	#142	Overall
	#12	Time Series DBMS

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Score	4.46
Rank	#71	Overall
	#5	Time Series DBMS

Website

github.com/Softmotions/ejdb

etcd.io
github.com/etcd-io/etcd

opentsdb.net

www.sqlite.org

www.timescale.com

Technical documentation

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

etcd.io/docs
github.com/etcd-io/etcd/tree/master/Documentation

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

www.sqlite.org/docs.html

docs.timescale.com

Developer

Softmotions

currently maintained by Yahoo and other contributors

Dwayne Richard Hipp

Timescale

Initial release

2012

2011

2000

2017

Current release

3.4, August 2019

3.46.0 (23 May 2024), May 2024

2.15.0, May 2024

License

Commercial or Open Source

Open Source

GPLv2

Open Source

Apache Version 2.0

Open Source

LGPL

Open Source

Public Domain

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

server-less

FreeBSD
Linux
Windows

experimental

Linux
Windows

server-less

Linux
OS X
Windows

Data scheme

schema-free

yes

dynamic column types

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

not rigid because of 'dynamic typing' concept.

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

SQL

Support of SQL

yes

SQL-92 is not fully supported

yes

full PostgreSQL SQL syntax

APIs and other access methods

in-process shared library

gRPC
JSON over HTTP

HTTP API
Telnet API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

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

.Net
C
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Rust
Scala
Tcl

Erlang
Go
Java
Python
R
Ruby

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes, watching key changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on HBase

none

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

none

Using Raft consensus algorithm to ensure data replication with strong consistency among multiple replicas.

selectable replication factor

based on HBase

none

Source-replica replication with hot standby and reads on replicas

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

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

via file-system locks

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

fine grained access rights according to SQL-standard

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