DBMS > GridGain vs. Snowflake vs. Splunk vs. TerminusDB

System Properties Comparison GridGain vs. Snowflake vs. Splunk vs. TerminusDB

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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

Analytics Platform for Big Data

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Search engine

Graph DBMS

Secondary database models

Document store
RDF store

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

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

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	86.45
Rank	#14	Overall
	#2	Search engines

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

Technical documentation

www.gridgain.com/docs/index.html

docs.snowflake.net/manuals/index.html

docs.splunk.com/Documentation/Splunk

terminusdb.github.io/terminusdb/#

Developer

GridGain Systems, Inc.

Snowflake Computing Inc.

Splunk Inc.

DataChemist Ltd.

Initial release

2007

2014

2003

2018

Current release

GridGain 8.5.1

11.0.0, January 2023

License

Commercial or Open Source

commercial

Limited free edition and free developer edition available

Open Source

GPL V3

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.

Implementation language

Java, C++, .Net

Prolog, Rust

Server operating systems

Linux
OS X
Solaris
Windows

hosted

Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

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

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.

yes

Secondary indexes

yes

SQL

Support of SQL

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

yes

Splunk Search Processing Language for search commands

SQL-like query language (WOQL)

APIs and other access methods

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

CLI Client
JDBC
ODBC

HTTP REST

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

C#
Java
JavaScript
PHP
Python
Ruby

JavaScript
Python

Server-side scripts

Stored procedures

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

user defined functions

yes

Triggers

yes (cache interceptors and events)

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

Multi-source replication

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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 journaling

In-memory capabilities

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

yes

User concepts

Access control

Security Hooks for custom implementations

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

Access rights for users and roles

Role-based access control

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