DBMS > GridGain vs. Kdb vs. Snowflake vs. YugabyteDB

System Properties Comparison GridGain vs. Kdb vs. Snowflake vs. YugabyteDB

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Editorial information provided by DB-Engines

Name

Description

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

Cloud-based data warehousing service for structured and semi-structured data

High-performance distributed SQL database for global, internet-scale applications. Wire and feature compatible with PostgreSQL.

Primary database model

Columnar
Key-value store
Object oriented DBMS
Relational DBMS

Time Series DBMS
Vector DBMS

Relational DBMS

Secondary database models

Relational DBMS

Document store
Wide column store

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

Score	1.48
Rank	#150	Overall
	#1	Columnar
	#26	Key-value stores
	#2	Object oriented DBMS
	#69	Relational DBMS

Score	7.73
Rank	#45	Overall
	#2	Time Series DBMS
	#1	Vector DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Score	2.48
Rank	#108	Overall
	#53	Relational DBMS

Website

Technical documentation

www.gridgain.com/docs/index.html

code.kx.com

docs.snowflake.net/manuals/index.html

docs.yugabyte.com
github.com/yugabyte/yugabyte-db

Developer

GridGain Systems, Inc.

Kx Systems, a division of First Derivatives plc

Snowflake Computing Inc.

Yugabyte Inc.

Initial release

2007

2000

kdb was released 2000, kdb+ in 2003

2014

2017

Current release

GridGain 8.5.1

3.6, May 2018

2.19, September 2023

License

Commercial or Open Source

commercial, open source

commercial

free 32-bit version

commercial

Open Source

Apache 2.0

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.

YugabyteDB Managed is the fully managed database-as-a-service offering of YugabyteDB. Get started quickly, and effortlessly ensure continuous availability and limitless scale of your cloud native applications.

Implementation language

Java, C++, .Net, Python, REST, SQL

C and C++

Server operating systems

Linux
OS X
Solaris
Windows
z/OS

Linux
OS X
Solaris
Windows

hosted

Linux
OS X

Data scheme

yes

support of semi-structured data formats (JSON, XML, Avro)

depending on used data model

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

table attribute 'grouped'

yes

SQL

Support of SQL

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

SQL-like query language (q)

yes

yes, PostgreSQL compatible

APIs and other access methods

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

HTTP API
JDBC
Jupyter
Kafka
ODBC
WebSocket

CLI Client
JDBC
ODBC

JDBC
YCQL, an SQL-based flexible-schema API with its roots in Cassandra Query Language
YSQL - a fully relational SQL API that is wire compatible with the SQL language in PostgreSQL

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C
C#
C++
Go
J
Java
JavaScript
Lua
MatLab
Perl
PHP
Python
R
Scala

JavaScript (Node.js)
Python

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Rust
Scala

Server-side scripts

Stored procedures

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

user defined functions

yes

sql, plpgsql, C

Triggers

yes (cache interceptors and events)

yes

with views

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

yes

Hash and Range Sharding, row-level geo-partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

Source-replica replication

yes

Based on Raft distributed consensus protocol, minimum 3 replicas for continuous availability

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

similar paradigm used for internal processing

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Strong consistency on writes and tunable consistency on reads

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Distributed ACID with Serializable & Snapshot Isolation. Inspired by Google Spanner architecture.

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

based on RocksDB

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Role-based access control
Security Hooks for custom implementations

rights management via user accounts

Users with fine-grained authorization concept, user roles and pluggable authentication

yes

More information provided by the system vendor

Specific characteristics

Integrated columnar database & programming system for streaming, real time and historical...
» more

YugabyteDB is an open source distributed SQL database for cloud native transactional...
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Competitive advantages

provides seamless scalability; runs on industry standard server platforms; is top-ranked...
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PostgreSQL compatible: Get instantly productive with a PostgreSQL compatible RDBMS....
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Typical application scenarios

tick database streaming sensor data massive intelligence applications oil and gas...
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Systems of record and engagement for cloud native applications that require resilience,...
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Key customers

Goldman Sachs Morgan Stanley Merrill Lynch J.P. Morgan Deutsche Bank IEX Securities...
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Market metrics

kdb+ performance and reliability proven by our customers in critical infrastructure...
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2 Million+ lifetime clusters deployed, 6.5K+ GitHub stars, 7K YugabyteDB Community...
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Licensing and pricing models

upon request
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Apache 2.0 license for the database
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