DBMS > DolphinDB vs. GigaSpaces vs. Postgres-XL vs. SAP HANA vs. TimesTen

System Properties Comparison DolphinDB vs. GigaSpaces vs. Postgres-XL vs. SAP HANA vs. TimesTen

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.

High performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented Transactions

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

In-memory, column based data store. Available as appliance or cloud service

In-Memory RDBMS compatible to Oracle

Primary database model

Time Series DBMS

Document store
Object oriented DBMS

Values are user defined objects

Relational DBMS

Secondary database models

Relational DBMS

Graph DBMS
Search engine

Document store
Spatial DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
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	1.03
Rank	#188	Overall
	#32	Document stores
	#6	Object oriented DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

www.dolphindb.com

www.gigaspaces.com

www.postgres-xl.org

www.sap.com/products/hana.html

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

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

docs.gigaspaces.com/latest/landing.html

www.postgres-xl.org/documentation

help.sap.com/hana

docs.oracle.com/database/timesten-18.1

Developer

DolphinDB, Inc

Gigaspaces Technologies

SAP

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2018

2000

2014

since 2012, originally named StormDB

2010

1998

Current release

v2.00.4, January 2022

15.5, September 2020

10 R1, October 2018

2.0 SPS07 (April 4, 2023), April 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

free community version available

Open Source

Apache Version 2; Commercial licenses available

Open Source

Mozilla public license

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Java, C++, .Net

Server operating systems

Linux
Windows

Linux
macOS
Solaris
Windows

Linux
macOS

Appliance or cloud-service

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
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.

XML can be used for describing objects metadata

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

SQL-99 for query and DML statements

yes

distributed, parallel query execution

yes

APIs and other access methods

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

GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

.Net
C++
Java
Python
Scala

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes

user defined functions

SQLScript, R

PL/SQL

Triggers

yes, event driven architecture

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

horizontal partitioning

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

synchronous or asynchronous
Source-replica replication

synchronous or asynchronous

yes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Map-Reduce pattern can be built with XAP task executors

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Consistency level configurable: ALL, QUORUM, ANY

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

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

Role-based access control

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard

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