DBMS > EXASOL vs. ObjectBox vs. OrientDB vs. Snowflake vs. Vitess

System Properties Comparison EXASOL vs. ObjectBox vs. OrientDB vs. Snowflake vs. Vitess

Editorial information provided by DB-Engines

Name

Description

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

Extremely fast embedded database for small devices, IoT and Mobile

Multi-model DBMS (Document, Graph, Key/Value)

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

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Relational DBMS

Object oriented DBMS

Document store
Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Time Series DBMS

Document store
Spatial DBMS

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

Score	1.76
Rank	#139	Overall
	#62	Relational DBMS

Score	1.29
Rank	#166	Overall
	#5	Object oriented DBMS

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.88
Rank	#203	Overall
	#95	Relational DBMS

Website

Technical documentation

www.exasol.com/resources

docs.objectbox.io

www.orientdb.com/docs/last/index.html

docs.snowflake.net/manuals/index.html

vitess.io/docs

Developer

Exasol

ObjectBox Limited

OrientDB LTD; CallidusCloud; SAP

Snowflake Computing Inc.

The Linux Foundation, PlanetScale

Initial release

2000

2017

2010

2014

2013

Current release

3.2.29, March 2024

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

Apache License 2.0

Open Source

Apache version 2

commercial

Open Source

Apache Version 2.0, commercial licenses available

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

C and C++

Java

Server operating systems

Android
iOS
Linux
macOS
Windows

All OS with a Java JDK (>= JDK 6)

hosted

Docker
Linux
macOS

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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

yes

SQL-like query language, no joins

yes

with proprietary extensions

APIs and other access methods

.Net
JDBC
ODBC
WebSocket

Proprietary native API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

CLI Client
JDBC
ODBC

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

Java
Lua
Python
R

C
C++
Dart
Go
Java
JavaScript

planned (as of Jan 2019)
Kotlin
Python

planned (as of Jan 2019)
Swift

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

Java, Javascript

user defined functions

yes

proprietary syntax

Triggers

yes

Hooks

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

online/offline synchronization between client and server

Multi-source replication

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

could be achieved with distributed queries

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

relationship in graphs

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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, groups and roles according to SQL-standard

yes

Access rights for users and roles; record level security configurable

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

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

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