DBMS > BoltDB vs. Heroic vs. LMDB vs. searchxml vs. Sequoiadb

System Properties Comparison BoltDB vs. Heroic vs. LMDB vs. searchxml vs. Sequoiadb

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

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

A high performant, light-weight, embedded key-value database library

DBMS for structured and unstructured content wrapped with an application server

NewSQL database with distributed OLTP and SQL

Primary database model

Key-value store

Time Series DBMS

Key-value store

Native XML DBMS
Search engine

Document store
Relational DBMS

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

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	1.99
Rank	#125	Overall
	#21	Key-value stores

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

github.com/boltdb/bolt

github.com/spotify/heroic

www.symas.com/symas-embedded-database-lmdb

www.searchxml.net/category/products

www.sequoiadb.com

Technical documentation

spotify.github.io/heroic

www.lmdb.tech/doc

www.searchxml.net/support/handouts

www.sequoiadb.com/en/index.php?m=Files&a=index

Developer

Spotify

Symas

informationpartners gmbh

Sequoiadb Ltd.

Initial release

2013

2014

2011

2015

2013

Current release

0.9.32, January 2024

1.0

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache 2.0

Open Source

commercial

Open Source

Server: AGPL; Client: Apache V2

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++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
Unix
Windows

Windows

Linux

Data scheme

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

SQL

Support of SQL

SQL-like query language

APIs and other access methods

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

RESTful HTTP API
WebDAV
XQuery
XSLT

proprietary protocol using JSON

Supported programming languages

.Net
C
C++
Clojure
Go
Haskell
Java
JavaScript (Node.js)
Lisp
Lua
MatLab
Nim
Objective C
OCaml
Perl
PHP
Python
R
Ruby
Rust
Swift
Tcl

C++

most other programming languages supported via APIs

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes

on the application server

JavaScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

none

yes

sychronisation to multiple collections

Source-replica replication

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

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

ACID

multiple readers, single writer

Document is locked during a transaction

Concurrency

Support for concurrent manipulation of data

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

Domain, group and role-based access control at the document level and for application services

simple password-based access control

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