DBMS > OpenEdge vs. QuestDB vs. SAP HANA vs. Sphinx

System Properties Comparison OpenEdge vs. QuestDB vs. SAP HANA vs. Sphinx

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

A high performance open source SQL database for time series data

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

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

Primary database model

Secondary database models

Relational 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	3.75
Rank	#88	Overall
	#47	Relational DBMS

Score	2.48
Rank	#115	Overall
	#9	Time Series DBMS

Score	45.84
Rank	#22	Overall
	#16	Relational DBMS

Score	6.03
Rank	#60	Overall
	#6	Search engines

Website

www.progress.com/openedge

questdb.io

www.sap.com/products/hana.html

sphinxsearch.com

Technical documentation

documentation.progress.com/output/ua/OpenEdge_latest

questdb.io/docs

help.sap.com/hana

sphinxsearch.com/docs

Developer

Progress Software Corporation

QuestDB Technology Inc

SAP

Sphinx Technologies Inc.

Initial release

1984

2014

2010

2001

Current release

OpenEdge 12.2, March 2020

2.0 SPS07 (April 4, 2023), April 2023

3.5.1, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

Open Source

GPL version 2, commercial licence available

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

Java (Zero-GC), C++, Rust

C++

Server operating systems

AIX
HP-UX
Linux
Solaris
Windows

Linux
macOS
Windows

Appliance or cloud-service

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Data scheme

yes

schema-free via InfluxDB Line Protocol

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

full-text index on all search fields

SQL

Support of SQL

yes

close to SQL 92

SQL with time-series extensions

yes

SQL-like query language (SphinxQL)

APIs and other access methods

JDBC
ODBC

HTTP REST
InfluxDB Line Protocol (TCP/UDP)
JDBC
PostgreSQL wire protocol

JDBC
ODBC

Proprietary protocol

Supported programming languages

Progress proprietary ABL (Advanced Business Language)

PostgreSQL driver
C++
Go
Java
JavaScript (Node.js)
Python
Rust

over HTTP

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Server-side scripts

Stored procedures

yes

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

since Version 11.4

horizontal partitioning (by timestamps)

yes

Sharding

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

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Source-replica replication with eventual consistency

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

ACID for single-table writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

through memory mapped files

yes

User concepts

Access control

Users and groups

yes

More information provided by the system vendor

Specific characteristics

Relational model with native time series support Column-based storage and time partitioned...
» more

Competitive advantages

High ingestion throughput: peak of 4M rows/sec (TSBS Benchmark) Code optimizations...
» more

Typical application scenarios

Financial tick data Industrial IoT Application Metrics Monitoring
» more

Key customers

Banks & Hedge funds, Yahoo, OKX, Airbus, Aquis Exchange, Net App, Cloudera, Airtel,...
» more

Licensing and pricing models

Open source Apache 2.0 QuestDB Enterprise QuestDB Cloud
» more

News

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27 March 2024

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