DBMS > Badger vs. Heroic vs. VoltDB vs. Warp 10

System Properties Comparison Badger vs. Heroic vs. VoltDB vs. Warp 10

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Editorial information provided by DB-Engines

Name

Description

An embeddable, persistent, simple and fast Key-Value Store, written purely in Go.

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

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

Score	0.22
Rank	#320	Overall
	#47	Key-value stores

Score	0.46
Rank	#265	Overall
	#22	Time Series DBMS

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Score	0.14
Rank	#344	Overall
	#32	Time Series DBMS

Website

github.com/dgraph-io/badger

github.com/spotify/heroic

www.voltdb.com

www.warp10.io

Technical documentation

godoc.org/github.com/dgraph-io/badger

spotify.github.io/heroic

docs.voltdb.com

www.warp10.io/content/02_Getting_started

Developer

DGraph Labs

Spotify

VoltDB Inc.

SenX

Initial release

2017

2014

2010

2015

Current release

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache 2.0

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Open Source

Apache License 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

Java, C++

Java

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
OS X

for development

Linux
OS X
Windows

Data scheme

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

yes

SQL

Support of SQL

yes

only a subset of SQL 99

APIs and other access methods

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

Java API
JDBC
RESTful HTTP/JSON API

HTTP API
Jupyter
WebSocket

Supported programming languages

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Java

yes

WarpScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Multi-source replication
Source-replica replication

selectable replication factor

based on HBase

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

based on HBase

Foreign keys

Referential integrity

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

yes

Durability

Support for making data persistent

yes

Snapshots and command logging

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

Users and roles with access to stored procedures

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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