DBMS > BoltDB vs. Graph Engine vs. Heroic vs. Infobright vs. Tkrzw

System Properties Comparison BoltDB vs. Graph Engine vs. Heroic vs. Infobright vs. Tkrzw

Editorial information provided by DB-Engines

Name

Description

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

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

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Key-value store

Graph DBMS
Key-value store

Time Series DBMS

Relational DBMS

Key-value store

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

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

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

github.com/boltdb/bolt

www.graphengine.io

github.com/spotify/heroic

ignitetech.com/softwarelibrary/infobrightdb

dbmx.net/tkrzw

Technical documentation

www.graphengine.io/docs/manual

spotify.github.io/heroic

Developer

Microsoft

Spotify

Ignite Technologies Inc.; formerly InfoBright Inc.

Mikio Hirabayashi

Initial release

2013

2010

2014

2005

2020

Current release

0.9.3, August 2020

License

Commercial or Open Source

Open Source

MIT License

Open Source

MIT License

Open Source

Apache 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

Apache Version 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

.NET and C

Java

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

.NET

Linux
Windows

Linux
macOS

Data scheme

schema-free

yes

schema-free

yes

schema-free

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.

Secondary indexes

yes

via Elasticsearch

Knowledge Grid Technology used instead

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

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

ADO.NET
JDBC
ODBC

Supported programming languages

C#
C++
F#
Visual Basic

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Source-replica replication

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

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

In-memory capabilities

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

yes

using specific database classes

User concepts

Access control

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

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