DBMS > ClickHouse vs. GridGain vs. Microsoft Azure Cosmos DB vs. Splunk vs. Stardog

System Properties Comparison ClickHouse vs. GridGain vs. Microsoft Azure Cosmos DB vs. Splunk vs. Stardog

Editorial information provided by DB-Engines

Name

Description

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

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

Globally distributed, horizontally scalable, multi-model database service

Analytics Platform for Big Data

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Relational DBMS

Key-value store
Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Search engine

Graph DBMS
RDF store

Secondary database models

Time Series DBMS

Spatial DBMS

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

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

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

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	86.45
Rank	#14	Overall
	#2	Search engines

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

clickhouse.com

www.gridgain.com

azure.microsoft.com/services/cosmos-db

www.splunk.com

www.stardog.com

Technical documentation

clickhouse.com/docs

www.gridgain.com/docs/index.html

learn.microsoft.com/azure/cosmos-db

docs.splunk.com/Documentation/Splunk

docs.stardog.com

Developer

Clickhouse Inc.

GridGain Systems, Inc.

Microsoft

Splunk Inc.

Stardog-Union

Initial release

2016

2007

2014

2003

2010

Current release

v24.4.1.2088-stable, May 2024

GridGain 8.5.1

7.3.0, May 2020

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

Limited free edition and free developer edition available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.

Implementation language

C++

Java, C++, .Net

Java

Server operating systems

FreeBSD
Linux
macOS

Linux
OS X
Solaris
Windows

hosted

Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free

yes

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

JSON types

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

Import/export of XML data possible

Secondary indexes

yes

All properties auto-indexed by default

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

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

SQL-like query language

Splunk Search Processing Language for search commands

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

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

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

HTTP REST

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

C#
Java
JavaScript
PHP
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

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

JavaScript

yes

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes (cache interceptors and events)

JavaScript

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

Implicit feature of the cloud service

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

yes (replicated cache)

yes

Implicit feature of the cloud service

Multi-source replication

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

ACID

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

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

Security Hooks for custom implementations

Access rights can be defined down to the item level

Access rights for users and roles

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