DBMS > ClickHouse vs. GigaSpaces vs. Google Cloud Bigtable vs. Ignite vs. SAP SQL Anywhere

System Properties Comparison ClickHouse vs. GigaSpaces vs. Google Cloud Bigtable vs. Ignite vs. SAP SQL Anywhere

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.

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

Apache Ignite is a memory-centric distributed database, caching, and processing platform for transactional, analytical, and streaming workloads, delivering in-memory speeds at petabyte scale.

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Key-value store
Wide column store

Key-value store
Relational DBMS

Relational DBMS

Secondary database models

Time Series DBMS

Graph DBMS
Search engine

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

Score	15.55
Rank	#38	Overall
	#23	Relational DBMS

Score	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	3.11
Rank	#96	Overall
	#15	Key-value stores
	#49	Relational DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Website

clickhouse.com

www.gigaspaces.com

cloud.google.com/bigtable

ignite.apache.org

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

clickhouse.com/docs

docs.gigaspaces.com/latest/landing.html

cloud.google.com/bigtable/docs

apacheignite.readme.io/docs

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Clickhouse Inc.

Gigaspaces Technologies

Google

Apache Software Foundation

SAP

formerly Sybase

Initial release

2016

2000

2015

1992

Current release

v24.4.1.2088-stable, May 2024

15.5, September 2020

Apache Ignite 2.6

17, July 2015

License

Commercial or Open Source

Open Source

Apache 2.0

Open Source

Apache Version 2; Commercial licenses available

commercial

Open Source

Apache 2.0

commercial

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.

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.
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.

Implementation language

C++

Java, C++, .Net

C++, Java, .Net

Server operating systems

FreeBSD
Linux
macOS

Linux
macOS
Solaris
Windows

hosted

Linux
OS X
Solaris
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

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.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

SQL-99 for query and DML statements

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

yes

APIs and other access methods

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

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

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

ADO.NET
HTTP API
JDBC
ODBC

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

.Net
C++
Java
Python
Scala

C#
C++
Go
Java
JavaScript (Node.js)
Python

C#
C++
Java
PHP
Python
Ruby
Scala

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

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

yes, in C/C++, Java, .Net or Perl

Triggers

yes, event driven architecture

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

key based and custom

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Internal replication in Colossus, and regional replication between two clusters in different zones

yes (replicated cache)

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

yes

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-row operations

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.

Role-based access control

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Security Hooks for custom implementations

fine grained access rights according to SQL-standard

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