DBMS > Apache Druid vs. BoltDB vs. Heroic vs. InfinityDB vs. RocksDB

System Properties Comparison Apache Druid vs. BoltDB vs. Heroic vs. InfinityDB vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

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

An embedded key-value store for Go.

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

A Java embedded Key-Value Store which extends the Java Map interface

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Primary database model

Relational DBMS
Time Series DBMS

Key-value store

Time Series DBMS

Key-value store

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

Score	3.29
Rank	#95	Overall
	#49	Relational DBMS
	#7	Time Series DBMS

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

Score	0.57
Rank	#250	Overall
	#21	Time Series DBMS

Score	0.07
Rank	#359	Overall
	#54	Key-value stores

Score	4.00
Rank	#84	Overall
	#11	Key-value stores

Website

druid.apache.org

github.com/boltdb/bolt

github.com/spotify/heroic

boilerbay.com

rocksdb.org

Technical documentation

druid.apache.org/docs/latest/design

spotify.github.io/heroic

boilerbay.com/infinitydb/manual

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation and contributors

Spotify

Boiler Bay Inc.

Facebook, Inc.

Initial release

2012

2013

2014

2002

2013

Current release

29.0.1, April 2024

4.0

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache license v2

Open Source

MIT License

Open Source

Apache 2.0

commercial

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Unix

BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Linux

Data scheme

yes

schema-less columns are supported

schema-free

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

Typing

predefined data types such as float or date

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

SQL

Support of SQL

SQL for querying

APIs and other access methods

JDBC
RESTful HTTP/JSON API

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

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

C++ API
Java API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Java

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Sharding

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

none

yes

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

Eventual Consistency
Immediate Consistency

Immediate Consistency

READ-COMMITTED or SERIALIZED

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

yes

ACID

Optimistic locking for transactions; no isolation for bulk loads

yes

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

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

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