DBMS > atoti vs. DolphinDB vs. OrientDB vs. Snowflake vs. Teradata Aster

System Properties Comparison atoti vs. DolphinDB vs. OrientDB vs. Snowflake vs. Teradata Aster

Editorial information provided by DB-Engines

Name

Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

DolphinDB is a high performance Time Series DBMS. It is integrated with an easy-to-use fully featured programming language and a high-volume high-velocity streaming analytics system. It offers operational simplicity, scalability, fault tolerance, and concurrency.

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

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

Platform for big data analytics on multistructured data sources and types

Primary database model

Object oriented DBMS

Time Series DBMS

Document store
Graph DBMS
Key-value store

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.56
Rank	#245	Overall
	#10	Object oriented DBMS

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

Technical documentation

docs.atoti.io

docs.dolphindb.cn/en/help200/index.html

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

docs.snowflake.net/manuals/index.html

Developer

ActiveViam

DolphinDB, Inc

OrientDB LTD; CallidusCloud; SAP

Snowflake Computing Inc.

Teradata

Initial release

2018

2010

2014

2005

Current release

v2.00.4, January 2022

3.2.29, March 2024

License

Commercial or Open Source

commercial

free versions available

commercial

free community version available

Open Source

Apache version 2

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++

Java

Server operating systems

Linux
Windows

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

hosted

Linux

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)

Flexible Schema (defined schema, partial schema, schema free)

defined schema within the relational store; partial schema or schema free in the Aster File Store

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

in Aster File Store

Secondary indexes

yes

SQL

Support of SQL

Multidimensional Expressions (MDX)

SQL-like query language

SQL-like query language, no joins

yes

APIs and other access methods

JDBC
JSON over HTTP
Kafka
MQTT (Message Queue Telemetry Transport)
ODBC
OPC DA
OPC UA
RabbitMQ
WebSocket

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

CLI Client
JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB

Supported programming languages

C#
C++
Go
Java
JavaScript
MatLab
Python
R
Rust

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

JavaScript (Node.js)
Python

C
C#
C++
Java
Python
R

Server-side scripts

Stored procedures

Python

yes

Java, Javascript

user defined functions

R packages

Triggers

Hooks

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

horizontal partitioning

Sharding

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

yes

Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

could be achieved with distributed queries

yes

SQL Map-Reduce Framework

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

relationship in graphs

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

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

User concepts

Access control

Administrators, Users, Groups

Access rights for users and roles; record level security configurable

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

fine grained access rights according to SQL-standard

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