DBMS > DolphinDB vs. Google Cloud Spanner vs. H2 vs. KairosDB vs. OpenEdge

System Properties Comparison DolphinDB vs. Google Cloud Spanner vs. H2 vs. KairosDB vs. OpenEdge

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.

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

Distributed Time Series DBMS based on Cassandra or H2

Application development environment with integrated database management system

Primary database model

Secondary database models

Relational DBMS

Spatial DBMS

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

Score	4.13
Rank	#80	Overall
	#6	Time Series DBMS

Score	2.89
Rank	#103	Overall
	#52	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	0.62
Rank	#239	Overall
	#20	Time Series DBMS

Score	3.51
Rank	#86	Overall
	#46	Relational DBMS

Website

www.dolphindb.com

cloud.google.com/spanner

www.h2database.com

github.com/kairosdb/kairosdb

www.progress.com/openedge

Technical documentation

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

cloud.google.com/spanner/docs

www.h2database.com/html/main.html

kairosdb.github.io

documentation.progress.com/output/ua/OpenEdge_latest

Developer

DolphinDB, Inc

Google

Thomas Mueller

Progress Software Corporation

Initial release

2018

2017

2005

2013

1984

Current release

v2.00.4, January 2022

2.2.220, July 2023

1.2.2, November 2018

OpenEdge 12.2, March 2020

License

Commercial or Open Source

commercial

free community version available

commercial

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache 2.0

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++

Java

Server operating systems

Linux
Windows

hosted

All OS with a Java VM

Linux
OS X
Windows

AIX
HP-UX
Linux
Solaris
Windows

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.

yes

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

Query statements complying to ANSI 2011

yes

close to SQL 92

APIs and other access methods

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

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

JDBC
ODBC

Graphite protocol
HTTP REST
Telnet API

JDBC
ODBC

Supported programming languages

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

Go
Java
JavaScript (Node.js)
Python

Java

Java
JavaScript

Node.js
PHP
Python

Progress proprietary ABL (Advanced Business Language)

Server-side scripts

Stored procedures

yes

Java Stored Procedures and User-Defined Functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Sharding

based on Cassandra

horizontal partitioning

since Version 11.4

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication with 3 replicas for regional instances.

With clustering: 2 database servers on different computers operate on identical copies of a database

selectable replication factor

based on Cassandra

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

yes

ACID

Strict serializable isolation

ACID

Concurrency

Support for concurrent manipulation of data

yes

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, groups and roles based on Google Cloud Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

simple password-based access control

Users and groups

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