DBMS > OpenQM vs. Sequoiadb vs. Transwarp Hippo vs. XTDB

System Properties Comparison OpenQM vs. Sequoiadb vs. Transwarp Hippo vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

QpenQM is a high-performance, self-tuning, multi-value DBMS

NewSQL database with distributed OLTP and SQL

Cloud-native distributed Vector DBMS that supports storage, retrieval, and management of massive vector-based datasets

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Multivalue DBMS

Document store
Relational DBMS

Vector DBMS

Document store

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

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

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

Score	0.05
Rank	#386	Overall
	#15	Vector DBMS

Score	0.18
Rank	#332	Overall
	#46	Document stores

Website

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.sequoiadb.com

www.transwarp.cn/en/subproduct/hippo

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

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

www.xtdb.com/docs

Developer

Rocket Software, originally Martin Phillips

Sequoiadb Ltd.

Juxt Ltd.

Initial release

1993

2013

2023

2019

Current release

3.4-12

1.0, May 2023

1.19, September 2021

License

Commercial or Open Source

Open Source

GPLv2, extended commercial license available

Open Source

Server: AGPL; Client: Apache V2

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++

Clojure

Server operating systems

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

Linux

Linux
macOS

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

with some exceptions

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

Vector, Numeric and String

yes, extensible-data-notation format

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

SQL-like query language

limited SQL, making use of Apache Calcite

APIs and other access methods

proprietary protocol using JSON

RESTful HTTP API

HTTP REST
JDBC

Supported programming languages

.Net
Basic
C
Java
Objective C
PHP
Python

.Net
C++
Java
PHP
Python

C++
Java
Python

Clojure
Java

Server-side scripts

Stored procedures

yes

JavaScript

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

yes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes, each node contains all data

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

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Document is locked during a transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

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 can be defined down to the item level

simple password-based access control

Role based access control and fine grained access rights

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