DBMS > DolphinDB vs. GeoMesa vs. Google BigQuery vs. HEAVY.AI vs. Tibero

System Properties Comparison DolphinDB vs. GeoMesa vs. Google BigQuery vs. HEAVY.AI vs. Tibero

Editorial information provided by DB-Engines

Name

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.

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Large scale data warehouse service with append-only tables

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

A secure RDBMS, designed for easy portability from Oracle

Primary database model

Time Series DBMS

Spatial DBMS

Relational DBMS

Secondary database models

Relational DBMS

Spatial DBMS

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

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	0.86
Rank	#205	Overall
	#4	Spatial DBMS

Score	58.10
Rank	#19	Overall
	#13	Relational DBMS

Score	1.64
Rank	#145	Overall
	#67	Relational DBMS

Score	1.59
Rank	#148	Overall
	#68	Relational DBMS

Website

www.dolphindb.com

www.geomesa.org

cloud.google.com/bigquery

github.com/heavyai/heavydb
www.heavy.ai

us.tmaxsoft.com/products/tibero

Technical documentation

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

www.geomesa.org/documentation/stable/user/index.html

cloud.google.com/bigquery/docs

docs.heavy.ai

technet.tmaxsoft.com/upload/download/online/tibero/pver-20150504-000002/index.html

Developer

DolphinDB, Inc

CCRi and others

Google

HEAVY.AI, Inc.

TmaxSoft

Initial release

2018

2014

2010

2016

2003

Current release

v2.00.4, January 2022

5.0.0, May 2024

5.10, January 2022

6, April 2015

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache License 2.0

commercial

Open Source

Apache Version 2; enterprise edition available

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

C++

Scala

C++ and CUDA

C and Assembler

Server operating systems

Linux
Windows

hosted

Linux

AIX
HP-UX
Linux
Solaris
Windows

Data scheme

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

SQL-like query language

yes

APIs and other access methods

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

RESTful HTTP/JSON API

JDBC
ODBC
Thrift
Vega

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI

Supported programming languages

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

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

All languages supporting JDBC/ODBC/Thrift
Python

C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic

Server-side scripts

Stored procedures

yes

user defined functions

in JavaScript

Persistent Stored Procedure (PSM)

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

depending on storage layer

none

Sharding

Round robin

horizontal partitioning

by range, hash, list or composite

Replication methods

Methods for redundantly storing data on multiple nodes

yes

depending on storage layer

Multi-source replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Since BigQuery is designed for querying data

ACID

Concurrency

Support for concurrent manipulation of data

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

depending on storage layer

yes

planned for next version

User concepts

Access control

Administrators, Users, Groups

yes

depending on the DBMS used for storage

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

fine grained access rights according to SQL-standard

fine grained access rights according to SQL-standard (SQL 92, SQL 99)

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