DBMS > Apache Druid vs. EsgynDB vs. Interbase vs. Lovefield vs. ReductStore

System Properties Comparison Apache Druid vs. EsgynDB vs. Interbase vs. Lovefield vs. ReductStore

Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Light-weight proven RDBMS

originally from Borland

Embeddable relational database for web apps written in pure JavaScript

Designed to manage unstructured time-series data efficiently, providing unique features such as storing time-stamped blobs with labels, customizable data retention policies, and a straightforward FIFO quota system.

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Time Series DBMS

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	4.08
Rank	#75	Overall
	#41	Relational DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Website

druid.apache.org

www.esgyn.cn

www.embarcadero.com/products/interbase

google.github.io/lovefield

github.com/reductstore
www.reduct.store

Technical documentation

druid.apache.org/docs/latest/design

docs.embarcadero.com/products/interbase

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

www.reduct.store/docs

Developer

Apache Software Foundation and contributors

Esgyn

Embarcadero

Google

ReductStore LLC

Initial release

2012

2015

1984

2014

2023

Current release

29.0.1, April 2024

InterBase 2020, December 2019

2.1.12, February 2017

1.9, March 2024

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

Apache 2.0

Open Source

Business Source License 1.1

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

C++, Java

JavaScript

C++, Rust

Server operating systems

Linux
OS X
Unix

Linux

Android
iOS
Linux
OS X
Windows

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

tested with Chrome, Firefox, IE, Safari

Docker
Linux
macOS
Windows

Data scheme

yes

schema-less columns are supported

yes

Typing

predefined data types such as float or date

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.

export as XML data possible

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

yes

SQL-like query language

via JavaScript builder pattern

APIs and other access methods

JDBC
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

HTTP API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

All languages supporting JDBC/ODBC/ADO.Net

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

JavaScript

C++
JavaScript (Node.js)
Python
Rust

Server-side scripts

Stored procedures

Java Stored Procedures

yes

Interbase procedure and trigger language

Triggers

yes

Using read-only observers

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Multi-source replication between multi datacenters

Interbase Change Views

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

yes

Durability

Support for making data persistent

yes

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

In-memory capabilities

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

yes

using MemoryDB

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

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