DBMS > OpenMLDB vs. Sequoiadb vs. Spark SQL vs. TimesTen

System Properties Comparison OpenMLDB vs. Sequoiadb vs. Spark SQL vs. TimesTen

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Editorial information provided by DB-Engines

Name

Description

An open-source machine learning database that provides a feature platform for training and inference

NewSQL database with distributed OLTP and SQL

Spark SQL is a component on top of 'Spark Core' for structured data processing

In-Memory RDBMS compatible to Oracle

Primary database model

Time Series DBMS

Document store
Relational DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	0.10
Rank	#359	Overall
	#36	Time Series DBMS

Score	0.50
Rank	#258	Overall
	#41	Document stores
	#120	Relational DBMS

Score	18.04
Rank	#33	Overall
	#20	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

openmldb.ai

www.sequoiadb.com

spark.apache.org/sql

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

openmldb.ai/docs/zh/main

www.sequoiadb.com/en/index.php?m=Files&a=index

spark.apache.org/docs/latest/sql-programming-guide.html

docs.oracle.com/database/timesten-18.1

Developer

4 Paradigm Inc.

Sequoiadb Ltd.

Apache Software Foundation

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2020

2013

2014

1998

Current release

2024-2 February 2024

3.5.0 ( 2.13), September 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Server: AGPL; Client: Apache V2

Open Source

Apache 2.0

commercial

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

C++, Java, Scala

C++

Scala

Server operating systems

Linux

Linux
OS X
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Data scheme

Fixed schema

schema-free

yes

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

SQL-like query language

SQL-like DML and DDL statements

yes

APIs and other access methods

JDBC
SQLAlchemy

proprietary protocol using JSON

JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C++
Go
Java
Python
Scala

.Net
C++
Java
PHP
Python

Java
Python
R
Scala

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

JavaScript

PL/SQL

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

yes, utilizing Spark Core

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

Document is locked during a transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

fine grained access rights according to SQL-standard

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