DBMS > EXASOL vs. GigaSpaces vs. JaguarDB vs. Snowflake vs. Tibero

System Properties Comparison EXASOL vs. GigaSpaces vs. JaguarDB vs. Snowflake vs. Tibero

Editorial information provided by DB-Engines

Name

Description

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

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

Performant, highly scalable DBMS for AI and IoT applications

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

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Relational DBMS

Document store
Object oriented DBMS

Values are user defined objects

Key-value store
Vector DBMS

Relational DBMS

Secondary database models

Graph DBMS
Search engine

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

Score	2.25
Rank	#120	Overall
	#57	Relational DBMS

Score	1.02
Rank	#192	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.09
Rank	#356	Overall
	#53	Key-value stores
	#13	Vector DBMS

Score	123.20
Rank	#9	Overall
	#6	Relational DBMS

Score	1.81
Rank	#143	Overall
	#65	Relational DBMS

Website

us.tmaxsoft.com/products/tibero

Technical documentation

www.exasol.com/resources

docs.gigaspaces.com/latest/landing.html

www.jaguardb.com/support.html

docs.snowflake.net/manuals/index.html

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

Exasol

Gigaspaces Technologies

DataJaguar, Inc.

Snowflake Computing Inc.

TmaxSoft

Initial release

2000

2015

2014

2003

Current release

15.5, September 2020

3.3 July 2023

6, April 2015

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; Commercial licenses available

Open Source

GPL V3.0

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.

Implementation language

Java, C++, .Net

C++

the server part. Clients available in other languages

C and Assembler

Server operating systems

Linux
macOS
Solaris
Windows

Linux

hosted

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

yes

schema-free

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.

XML can be used for describing objects metadata

yes

Secondary indexes

yes

SQL

Support of SQL

yes

SQL-99 for query and DML statements

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

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

JDBC
ODBC

CLI Client
JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

Java
Lua
Python
R

.Net
C++
Java
Python
Scala

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

JavaScript (Node.js)
Python

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

user defined functions

yes

user defined functions

Persistent Stored Procedure (PSM)

Triggers

yes

yes, event driven architecture

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

Multi-source replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

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

planned for next version

User concepts

Access control

Access rights for users, groups and roles according to SQL-standard

Role-based access control

rights management via user accounts

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

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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