DBMS > DolphinDB vs. GreptimeDB vs. jBASE vs. SAP SQL Anywhere vs. Stardog

System Properties Comparison DolphinDB vs. GreptimeDB vs. jBASE vs. SAP SQL Anywhere vs. Stardog

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.

An open source Time Series DBMS built for increased scalability, high performance and efficiency

A robust multi-value DBMS comprising development tools and middleware

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Secondary database models

Relational DBMS

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

Score	4.03
Rank	#78	Overall
	#6	Time Series DBMS

Score	0.12
Rank	#351	Overall
	#34	Time Series DBMS

Score	1.49
Rank	#156	Overall
	#3	Multivalue DBMS

Score	3.95
Rank	#80	Overall
	#42	Relational DBMS

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

www.dolphindb.com

greptime.com

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

www.sap.com/products/technology-platform/sql-anywhere.html

www.stardog.com

Technical documentation

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

docs.greptime.com

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

help.sap.com/docs/SAP_SQL_Anywhere

docs.stardog.com

Developer

DolphinDB, Inc

Greptime Inc.

Rocket Software (formerly Zumasys)

SAP

formerly Sybase

Stardog-Union

Initial release

2018

2022

1991

1992

2010

Current release

v2.00.4, January 2022

5.7

17, July 2015

7.3.0, May 2020

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache Version 2.0

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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++

Rust

Java

Server operating systems

Linux
Windows

Android
Docker
FreeBSD
Linux
macOS
Windows

AIX
Linux
Windows

AIX
HP-UX
Linux
OS X
Solaris
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free, schema definition possible

schema-free

yes

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

yes

optional

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

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

SQL-like query language

yes

Embedded SQL for jBASE in BASIC

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

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

gRPC
HTTP API
JDBC

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

ADO.NET
HTTP API
JDBC
ODBC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

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

C++
Erlang
Go
Java
JavaScript

.Net
Basic
Jabbascript
Java

C
C#
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

yes

Python

yes

yes, in C/C++, Java, .Net or Perl

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Database mirroring

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

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 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

Simple rights management via user accounts

Access rights can be defined down to the item level

fine grained access rights according to SQL-standard

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

GreptimeDB is a SQL & Python-enabled timeseries database system built from scratch...
» more

Competitive advantages

- Inherits advantages of Rust, such as excellent performance, memory safe, resource...
» more

Typical application scenarios

For IoT industries, GreptimeDB can seamless integrate with message queues and other...
» more

Key customers

Greptime's clients span multiple sectors including IoT, connected vehicles, and energy...
» more

Market metrics

GreptimeDB has garnered global recognition by topping GitHub trends following its...
» more

Licensing and pricing models

GreptimeDB: open source, distributed, cloud-native TSDB; supports Hybrid Time-series...
» more

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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