DBMS > EXASOL vs. GreptimeDB vs. JaguarDB vs. SAP IQ vs. VoltDB

System Properties Comparison EXASOL vs. GreptimeDB vs. JaguarDB vs. SAP IQ vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

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

An open source Time Series DBMS built for increased scalability, high performance and efficiency

Performant, highly scalable DBMS for AI and IoT applications

Columnar RDBMS optimized for Big Data analytics

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Relational DBMS

Time Series DBMS

Key-value store
Vector DBMS

Relational DBMS

column-oriented

Relational DBMS

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

Score	1.99
Rank	#124	Overall
	#58	Relational DBMS

Score	0.06
Rank	#352	Overall
	#33	Time Series DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	2.75
Rank	#104	Overall
	#53	Relational DBMS

Score	1.44
Rank	#158	Overall
	#73	Relational DBMS

Website

www.exasol.com

greptime.com

www.jaguardb.com

www.sap.com/products/technology-platform/sybase-iq-big-data-management.html

www.voltdb.com

Technical documentation

www.exasol.com/resources

docs.greptime.com

www.jaguardb.com/support.html

help.sap.com/docs/SAP_IQ

docs.voltdb.com

Developer

Exasol

Greptime Inc.

DataJaguar, Inc.

SAP, formerly Sybase

VoltDB Inc.

Initial release

2000

2022

2015

1994

2010

Current release

3.3 July 2023

16.1 SPS04, April 2019

11.3, April 2022

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

GPL V3.0

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Rust

C++

the server part. Clients available in other languages

Java, C++

Server operating systems

Android
Docker
FreeBSD
Linux
macOS
Windows

Linux

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X

for development

Data scheme

yes

schema-free, schema definition possible

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.

Secondary indexes

yes

SQL

Support of SQL

yes

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

only a subset of SQL 99

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

gRPC
HTTP API
JDBC

JDBC
ODBC

ADO.NET
JDBC
ODBC
RESTful HTTP API

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Java
Lua
Python
R

C++
Erlang
Go
Java
JavaScript

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

C
C#
C++
Java
Perl
PHP
Python
Ruby

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

user defined functions

Python

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

shared disk or shared nothing architectures with SAP IQ Multiplexer

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

SAP/Sybase Replication Server

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

Snapshots and command logging

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, groups and roles according to SQL-standard

Simple rights management via user accounts

rights management via user accounts

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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