DBMS > Heroic vs. Lovefield vs. ReductStore vs. SiriDB vs. Solr

System Properties Comparison Heroic vs. Lovefield vs. ReductStore vs. SiriDB vs. Solr

Editorial information provided by DB-Engines

Name

Description

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

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.

Open Source Time Series DBMS

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

Primary database model

Secondary database models

Spatial DBMS

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

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.33
Rank	#286	Overall
	#131	Relational DBMS

Score	0.05
Rank	#384	Overall
	#44	Time Series DBMS

Score	0.07
Rank	#378	Overall
	#42	Time Series DBMS

Score	41.02
Rank	#24	Overall
	#3	Search engines

Website

github.com/spotify/heroic

google.github.io/lovefield

github.com/reductstore
www.reduct.store

siridb.com

solr.apache.org

Technical documentation

spotify.github.io/heroic

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

www.reduct.store/docs

docs.siridb.com

solr.apache.org/resources.html

Developer

Spotify

Google

ReductStore LLC

Cesbit

Apache Software Foundation

Initial release

2014

2023

2017

2006

Current release

2.1.12, February 2017

1.9, March 2024

9.6.1, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

Business Source License 1.1

Open Source

MIT License

Open Source

Apache Version 2

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

JavaScript

C++, Rust

Java

Server operating systems

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

tested with Chrome, Firefox, IE, Safari

Docker
Linux
macOS
Windows

Linux

All OS with a Java VM

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

Data scheme

schema-free

yes

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

Typing

predefined data types such as float or date

yes

Numeric data

yes

supports customizable data types and automatic typing

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

via Elasticsearch

yes

All search fields are automatically indexed

SQL

Support of SQL

SQL-like query language

via JavaScript builder pattern

Solr Parallel SQL Interface

APIs and other access methods

HQL (Heroic Query Language, a JSON-based language)
HTTP API

HTTP API

Java API
RESTful HTTP/JSON API

Supported programming languages

JavaScript

C++
JavaScript (Node.js)
Python
Rust

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

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

Server-side scripts

Stored procedures

Java plugins

Triggers

Using read-only observers

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes

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

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

using MemoryDB

yes

User concepts

Access control

simple rights management via user accounts

yes

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