DBMS > Amazon Redshift vs. Interbase vs. NSDb vs. OceanBase vs. Sphinx

System Properties Comparison Amazon Redshift vs. Interbase vs. NSDb vs. OceanBase vs. Sphinx

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Light-weight proven RDBMS

originally from Borland

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

A distributed, high available RDBMS compatible with Oracle and MySQL

Open source search engine for searching in data from different sources, e.g. relational databases

Primary database model

Secondary database models

Document store
Wide column store

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	4.08
Rank	#75	Overall
	#41	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	1.57
Rank	#149	Overall
	#69	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Website

aws.amazon.com/redshift

www.embarcadero.com/products/interbase

nsdb.io

en.oceanbase.com

sphinxsearch.com

Technical documentation

docs.aws.amazon.com/redshift

docs.embarcadero.com/products/interbase

nsdb.io/Architecture

en.oceanbase.com/docs/oceanbase-database

sphinxsearch.com/docs

Developer

Amazon (based on PostgreSQL)

Embarcadero

OceanBase

previously Alibaba and Ant Group

Sphinx Technologies Inc.

Initial release

2012

1984

2017

2010

2001

Current release

InterBase 2020, December 2019

4.3.0, April 2024

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

Open Source

Commercial license available

Open Source

GPL version 2, commercial licence available

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

Java, Scala

C++

Server operating systems

hosted

Android
iOS
Linux
OS X
Windows

Linux
macOS

Linux

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

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.

export as XML data possible

yes

Secondary indexes

restricted

yes

all fields are automatically indexed

yes

full-text index on all search fields

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL-like query language

yes

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

gRPC
HTTP REST
WebSocket

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table API

Proprietary protocol

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby

Java
Scala

Ada

in MySQL-compatible model
C

in Oracle- and MySQL- compatible models
C++

in Oracle- and MySQL- compatible models
D

in MySQL-compatible model
Delphi

in MySQL-compatible model
Eiffel

in MySQL-compatible model
Erlang

in MySQL-compatible model
Haskell

in MySQL-compatible model
Java

in Oracle- and MySQL- compatible models
JavaScript (Node.js)

in MySQL-compatible model
Objective-C

in MySQL-compatible model
OCaml

in MySQL-compatible model
Perl

in MySQL-compatible model
PHP

in MySQL-compatible model
Python

in MySQL-compatible model
Ruby

in MySQL-compatible model
Scheme

in MySQL-compatible model
Tcl

in MySQL-compatible model

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Interbase procedure and trigger language

PL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible mode

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

horizontal partitioning (by hash, key, range, range columns, list, and list columns)

Sharding

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Interbase Change Views

Multi-source replication using Paxos

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Multiversion concurreny control

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

The original contents of fields are not stored in the Sphinx index.

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

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