DBMS > Apache Druid vs. GridGain vs. Kinetica vs. RocksDB vs. SwayDB

System Properties Comparison Apache Druid vs. GridGain vs. Kinetica vs. RocksDB vs. SwayDB

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

GridGain is an in-memory computing platform, built on Apache Ignite

Fully vectorized database across both GPUs and CPUs

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

An embeddable, non-blocking, type-safe key-value store for single or multiple disks and in-memory storage

Primary database model

Relational DBMS
Time Series DBMS

Key-value store
Relational DBMS

Relational DBMS

Key-value store

Secondary database models

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	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	0.64
Rank	#236	Overall
	#109	Relational DBMS

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

Score	0.00
Rank	#382	Overall
	#59	Key-value stores

Website

Technical documentation

druid.apache.org/docs/latest/design

www.gridgain.com/docs/index.html

docs.kinetica.com

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation and contributors

GridGain Systems, Inc.

Kinetica

Facebook, Inc.

Simer Plaha

Initial release

2012

2007

2012

2013

2018

Current release

29.0.1, April 2024

GridGain 8.5.1

7.1, August 2021

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

BSD

Open Source

GNU Affero GPL V3.0

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

Java

Java, C++, .Net

C, C++

C++

Scala

Server operating systems

Linux
OS X
Unix

Linux
OS X
Solaris
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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL for querying

ANSI-99 for query and DML statements, subset of DDL

SQL-like DML and DDL statements

APIs and other access methods

JDBC
RESTful HTTP/JSON API

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

JDBC
ODBC
RESTful HTTP API

C++ API
Java API

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

C#
C++
Java
PHP
Python
Ruby
Scala

C++
Java
JavaScript (Node.js)
Python

C
C++
Go
Java
Perl
Python
Ruby

Java
Kotlin
Scala

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

user defined functions

Triggers

yes (cache interceptors and events)

yes

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes (replicated cache)

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Atomic execution of operations

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

Security Hooks for custom implementations

Access rights for users and roles on table level

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