DBMS > Apache Druid vs. Kinetica vs. MaxDB vs. RavenDB vs. RocksDB

System Properties Comparison Apache Druid vs. Kinetica vs. MaxDB vs. RavenDB 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

Fully vectorized database across both GPUs and CPUs

A robust and reliable RDBMS optimized to run all major SAP solutions

Open Source Operational and Transactional Enterprise NoSQL Document Database

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

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Document store

Key-value store

Secondary database models

Spatial DBMS
Time Series DBMS

Graph DBMS
Spatial DBMS
Time Series 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	0.64
Rank	#236	Overall
	#109	Relational DBMS

Score	2.32
Rank	#112	Overall
	#55	Relational DBMS

Score	2.92
Rank	#101	Overall
	#18	Document stores

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Website

Technical documentation

druid.apache.org/docs/latest/design

docs.kinetica.com

maxdb.sap.com/documentation

ravendb.net/docs

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation and contributors

Kinetica

SAP, acquired from Software AG (Adabas-D) in 1997

Hibernating Rhinos

Facebook, Inc.

Initial release

2012

1984

2010

2013

Current release

29.0.1, April 2024

7.1, August 2021

7.9.10.12, February 2024

5.4, July 2022

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Limited community edition free

Open Source

AGPL version 3, commercial license available

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, C++

C++

Server operating systems

Linux
OS X
Unix

Linux

AIX
HP-UX
Linux
Solaris
Windows

Linux
macOS
Raspberry Pi
Windows

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-like DML and DDL statements

yes

SQL-like query language (RQL)

APIs and other access methods

JDBC
RESTful HTTP/JSON API

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
WebDAV

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

C++ API
Java API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C++
Java
JavaScript (Node.js)
Python

.Net
C#
Java
Perl
PHP
Python

.Net
C#
F#
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

none

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

Source-replica replication

Multi-source replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

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

GPU vRAM or System RAM

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 on table level

fine grained access rights according to SQL-standard

Authorization levels configured per client per database

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