DBMS > Apache Phoenix vs. Heroic vs. LokiJS vs. Manticore Search vs. SQLite

System Properties Comparison Apache Phoenix vs. Heroic vs. LokiJS vs. Manticore Search vs. SQLite

Editorial information provided by DB-Engines

Name

Description

A scale-out RDBMS with evolutionary schema built on Apache HBase

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

In-memory JavaScript DBMS

Multi-storage database for search, including full-text search.

Widely used embeddable, in-process RDBMS

Primary database model

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	2.06
Rank	#123	Overall
	#58	Relational DBMS

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	0.49
Rank	#260	Overall
	#42	Document stores

Score	0.29
Rank	#302	Overall
	#21	Search engines

Score	111.41
Rank	#10	Overall
	#7	Relational DBMS

Website

phoenix.apache.org

github.com/spotify/heroic

github.com/techfort/LokiJS

manticoresearch.com

www.sqlite.org

Technical documentation

phoenix.apache.org

spotify.github.io/heroic

techfort.github.io/LokiJS

manual.manticoresearch.com

www.sqlite.org/docs.html

Developer

Apache Software Foundation

Spotify

Manticore Software

Dwayne Richard Hipp

Initial release

2014

2017

2000

Current release

5.0-HBase2, July 2018 and 4.15-HBase1, December 2019

6.0, February 2023

3.46.0 (23 May 2024), May 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Open Source

GPL version 2

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

JavaScript

C++

Server operating systems

Linux
Unix
Windows

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

FreeBSD
Linux
macOS
Windows

server-less

Data scheme

yes

late-bound, schema-on-read capabilities

schema-free

Fixed schema

yes

dynamic column types

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

yes

not rigid because of 'dynamic typing' concept.

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.

Can index from XML

Secondary indexes

yes

via Elasticsearch

yes

via views

yes

full-text index on all search fields

yes

SQL

Support of SQL

yes

SQL-like query language

yes

SQL-92 is not fully supported

APIs and other access methods

JDBC

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

JavaScript API

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

C
C#
C++
Go
Groovy
Java
PHP
Python
Scala

JavaScript

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

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

Server-side scripts

Stored procedures

user defined functions

View functions in JavaScript

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Partitioning is done manually, search queries against distributed index is supported

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

yes

none

Synchronous replication based on Galera library

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency
Immediate Consistency

none

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

atomic operations within a single collection possible

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

via file-system locks

Durability

Support for making data persistent

yes

Serialization of a DB in a Node.JS/Cordova/PhoneGap environment. Usage of the IndexedDB-API in a browser.

yes

The original contents of fields are not stored in the Manticore index.

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

Access Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancy

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