DBMS > Apache Druid vs. FeatureBase vs. LeanXcale vs. RocksDB

System Properties Comparison Apache Druid vs. FeatureBase vs. LeanXcale vs. RocksDB

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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

Real-time database platform that powers real-time analytics and machine learning applications by simultaneously executing low-latency, high-throughput, and highly concurrent workloads.

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

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

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Key-value store
Relational DBMS

Key-value store

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

Score	3.25
Rank	#90	Overall
	#47	Relational DBMS
	#7	Time Series DBMS

Score	0.31
Rank	#292	Overall
	#135	Relational DBMS

Score	0.36
Rank	#280	Overall
	#40	Key-value stores
	#129	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Website

Technical documentation

druid.apache.org/docs/latest/design

docs.featurebase.com

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation and contributors

Molecula and Pilosa Open Source Contributors

LeanXcale

Facebook, Inc.

Initial release

2012

2017

2015

2013

Current release

29.0.1, April 2024

2022, May 2022

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

BSD

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

Linux
OS X
Unix

Linux
macOS

Linux

Data scheme

yes

schema-less columns are supported

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

SQL

Support of SQL

SQL for querying

SQL queries

yes

through Apache Derby

APIs and other access methods

JDBC
RESTful HTTP/JSON API

gRPC
JDBC
Kafka Connector
ODBC

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

C++ API
Java API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

Java
Python

C
Java
Scala

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

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using Linux fsync

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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