DBMS > BoltDB vs. EJDB vs. Heroic vs. mSQL vs. Spark SQL

System Properties Comparison BoltDB vs. EJDB vs. Heroic vs. mSQL vs. Spark SQL

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

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

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

mSQL (Mini SQL) is a simple and lightweight RDBMS

Spark SQL is a component on top of 'Spark Core' for structured data processing

Primary database model

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

Score	0.76
Rank	#224	Overall
	#32	Key-value stores

Score	0.30
Rank	#294	Overall
	#44	Document stores

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	1.67
Rank	#151	Overall
	#70	Relational DBMS

Score	19.15
Rank	#33	Overall
	#20	Relational DBMS

Website

github.com/boltdb/bolt

github.com/Softmotions/ejdb

github.com/spotify/heroic

hughestech.com.au/products/msql

spark.apache.org/sql

Technical documentation

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

spotify.github.io/heroic

spark.apache.org/docs/latest/sql-programming-guide.html

Developer

Softmotions

Spotify

Hughes Technologies

Apache Software Foundation

Initial release

2013

2012

2014

1994

2014

Current release

4.4, October 2021

3.5.0 ( 2.13), September 2023

License

Commercial or Open Source

Open Source

MIT License

Open Source

GPLv2

Open Source

Apache 2.0

commercial

free licenses can be provided

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

Scala

Server operating systems

BSD
Linux
OS X
Solaris
Windows

server-less

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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.

Secondary indexes

yes

via Elasticsearch

yes

SQL

Support of SQL

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

SQL-like DML and DDL statements

APIs and other access methods

in-process shared library

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

JDBC
ODBC

Supported programming languages

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

C
C++
Delphi
Java
Perl
PHP
Tcl

Java
Python
R
Scala

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

yes, utilizing Spark Core

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

none

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

yes

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.

User concepts

Access control

More information provided by the system vendor

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