DBMS > Apache Druid vs. Badger vs. Oracle NoSQL vs. VoltDB vs. Yaacomo

System Properties Comparison Apache Druid vs. Badger vs. Oracle NoSQL vs. VoltDB vs. Yaacomo

Editorial information provided by DB-Engines

Name

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

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

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Relational DBMS
Time Series DBMS

Key-value store

Document store
Key-value store
Relational DBMS

Relational DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	0.14
Rank	#331	Overall
	#49	Key-value stores

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

druid.apache.org

github.com/dgraph-io/badger

www.oracle.com/database/nosql/technologies/nosql

www.voltdb.com

yaacomo.com

Technical documentation

druid.apache.org/docs/latest/design

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

docs.oracle.com/en/database/other-databases/nosql-database/index.html

docs.voltdb.com

Developer

Apache Software Foundation and contributors

DGraph Labs

Oracle

VoltDB Inc.

Q2WEB GmbH

Initial release

2012

2017

2011

2010

2009

Current release

29.0.1, April 2024

23.3, December 2023

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

Apache 2.0

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

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

commercial

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++

Server operating systems

Linux
OS X
Unix

BSD
Linux
OS X
Solaris
Windows

Linux
Solaris SPARC/x86

Linux
OS X

for development

Android
Linux
Windows

Data scheme

yes

schema-less columns are supported

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

Typing

predefined data types such as float or date

yes

optional

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

SQL

Support of SQL

SQL for querying

SQL-like DML and DDL statements

yes

only a subset of SQL 99

yes

APIs and other access methods

JDBC
RESTful HTTP/JSON API

RESTful HTTP API

Java API
JDBC
RESTful HTTP/JSON API

JDBC
ODBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C
C#
Go
Java
JavaScript (Node.js)
Python

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency
Immediate Consistency

depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

FOREIGN KEY constraints are not supported

yes

Transaction concepts

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

configurable

ACID within a storage node (=shard)

ACID

Transactions are executed single-threaded within stored procedures

ACID

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

off heap cache

yes

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

Access rights for users and roles

Users and roles with access to stored procedures

fine grained access rights according to SQL-standard

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