DBMS > GBase vs. Hazelcast vs. NSDb vs. Postgres-XL vs. TimesTen

System Properties Comparison GBase vs. Hazelcast vs. NSDb vs. Postgres-XL vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

A widely adopted in-memory data grid

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

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

In-Memory RDBMS compatible to Oracle

Primary database model

Secondary database models

Document store

JSON support with IMDG 3.12

Document store
Spatial DBMS

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

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	5.46
Rank	#61	Overall
	#7	Key-value stores

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	0.53
Rank	#254	Overall
	#117	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

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

Technical documentation

hazelcast.org/imdg/docs

nsdb.io/Architecture

www.postgres-xl.org/documentation

docs.oracle.com/database/timesten-18.1

Developer

General Data Technology Co., Ltd.

Hazelcast

Oracle, TimesTen Performance Software, HP

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

Initial release

2004

2008

2017

2014

since 2012, originally named StormDB

1998

Current release

GBase 8a, GBase 8s, GBase 8c

5.3.6, November 2023

10 R1, October 2018

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

Apache Version 2; commercial licenses available

Open Source

Apache Version 2.0

Open Source

Mozilla public license

commercial

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, Java, Python

Java

Java, Scala

Server operating systems

Linux

All OS with a Java VM

Linux
macOS

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

yes: int, bigint, decimal, string

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

the object must implement a serialization strategy

yes

XML type, but no XML query functionality

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

Standard with numerous extensions

SQL-like query language

yes

distributed, parallel query execution

yes

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

JCache
JPA
Memcached protocol
RESTful HTTP API

gRPC
HTTP REST
WebSocket

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala

Java
Scala

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

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

user defined functions

yes

Event Listeners, Executor Services

user defined functions

PL/SQL

Triggers

yes

Events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Replicated Map

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

Immediate Consistency or Eventual Consistency selectable by user

Raft Consensus Algorithm

Eventual Consistency

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

ACID

one or two-phase-commit; repeatable reads; read commited

ACID

MVCC

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

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

yes

Role-based access control

fine grained access rights according to SQL-standard

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