DBMS > EJDB vs. Prometheus vs. Solr vs. TimescaleDB

System Properties Comparison EJDB vs. Prometheus vs. Solr vs. TimescaleDB

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Editorial information provided by DB-Engines

Name

Description

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

Open-source TimeSeries DBMS and monitoring system

A widely used distributed, scalable search engine based on Apache Lucene

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	0.27
Rank	#263	Overall
	#38	Document stores

Score	5.76
Rank	#62	Overall
	#3	Time Series DBMS

Score	50.69
Rank	#20	Overall
	#3	Search engines

Score	2.86
Rank	#100	Overall
	#6	Time Series DBMS

Website

ejdb.org

prometheus.io

lucene.apache.org/solr

www.timescale.com

Technical documentation

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

prometheus.io/docs

lucene.apache.org/solr/resources.html

docs.timescale.com

Developer

Softmotions

Apache Software Foundation

Timescale

Initial release

2012

2015

2006

2017

Current release

8.8.0, January 2021

License

Commercial or Open Source

Open Source

GPLv2

Open Source

Apache 2.0

Open Source

Apache Version 2

Open Source

Apache 2.0

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

Server operating systems

server-less

Linux
Windows

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Linux
OS X
Windows

Data scheme

schema-free

yes

Dynamic Fields enables on-the-fly addition of new fields

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

Numeric data only

yes

supports customizable data types and automatic typing

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.

Import of XML data possible

yes

Secondary indexes

yes

All search fields are automatically indexed

yes

SQL

Support of SQL

Solr Parallel SQL Interface

yes

full PostgreSQL SQL syntax

APIs and other access methods

in-process shared library

RESTful HTTP/JSON API

Java API
RESTful HTTP/JSON API

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++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Java plugins

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

User configurable commands triggered on index changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

by Federation

yes

Source-replica replication with hot standby and reads on replicas

MapReduce

Offers an API for user-defined Map/Reduce methods

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency

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

optimistic locking

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

fine grained access rights according to SQL-standard

More information provided by the system vendor

Specific characteristics

Timescale is the creator of TimescaleDB , the first open-source relational database...
» more

Competitive advantages

TimescaleDB is purpose-built to scale and handle time-series data workloads and is...
» more

Typical application scenarios

DevOps and Infrastructure Monitoring All monitoring data is time-series data. Efficiently...
» more

Key customers

TransferWise, Maersk, AppDynamics, Walmart, Comcast, LaunchDarkly, IBM, NOV, Cisco,...
» more

Market metrics

With over 9,000 GitHub stars and growing, 600,000 active databases, and an active...
» more

Licensing and pricing models

TimescaleDB comes in 3 versions, including fully managed Cloud-hosted solutions*,...
» more

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