DBMS > DolphinDB vs. Hive vs. TempoIQ vs. TerminusDB

System Properties Comparison DolphinDB vs. Hive vs. TempoIQ vs. TerminusDB

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Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be removed from the DB-Engines ranking.

Description

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.

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Primary database model

Secondary database models

Relational DBMS

Document store
RDF store

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

Score	4.23
Rank	#82	Overall
	#6	Time Series DBMS

Score	62.59
Rank	#18	Overall
	#12	Relational DBMS

Score	0.22
Rank	#323	Overall
	#28	Graph DBMS

Website

www.dolphindb.com

hive.apache.org

tempoiq.com (offline)

terminusdb.com

Technical documentation

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

cwiki.apache.org/confluence/display/Hive/Home

terminusdb.github.io/terminusdb/#

Developer

DolphinDB, Inc

Apache Software Foundation

initially developed by Facebook

TempoIQ

DataChemist Ltd.

Initial release

2018

2012

2018

Current release

v2.00.4, January 2022

3.1.3, April 2022

11.0.0, January 2023

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache Version 2

commercial

Open Source

GPL V3

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++

Java

Prolog, Rust

Server operating systems

Linux
Windows

All OS with a Java VM

Linux

Data scheme

yes

schema-free

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

SQL-like query language

SQL-like DML and DDL statements

SQL-like query language (WOQL)

APIs and other access methods

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

JDBC
ODBC
Thrift

HTTP API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

Supported programming languages

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

C++
Java
PHP
Python

C#
Java
JavaScript

Node.js
Python
Ruby

JavaScript
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Realtime Alerts

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Graph Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Journaling Streams

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory journaling

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, groups and roles

simple authentication-based access control

Role-based access control

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More resources

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