DBMS > chDB vs. Elasticsearch vs. SAP HANA vs. Sphinx vs. VoltDB

System Properties Comparison chDB vs. Elasticsearch vs. SAP HANA vs. Sphinx vs. VoltDB

Editorial information provided by DB-Engines

Name

Description

An embedded SQL OLAP Engine powered by ClickHouse

A distributed, RESTful modern search and analytics engine based on Apache Lucene

Elasticsearch lets you perform and combine many types of searches such as structured, unstructured, geo, and metric

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

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Secondary database models

Time Series DBMS

Document store
Spatial DBMS
Vector 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	0.07
Rank	#376	Overall
	#158	Relational DBMS

Score	132.83
Rank	#7	Overall
	#1	Search engines

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	5.95
Rank	#55	Overall
	#5	Search engines

Score	1.47
Rank	#157	Overall
	#73	Relational DBMS

Website

github.com/chdb-io/chdb

www.elastic.co/elasticsearch

www.sap.com/products/hana.html

sphinxsearch.com

www.voltdb.com

Technical documentation

doc.chdb.io

www.elastic.co/guide/en/elasticsearch/reference/current/index.html

help.sap.com/hana

sphinxsearch.com/docs

docs.voltdb.com

Developer

Elastic

SAP

Sphinx Technologies Inc.

VoltDB Inc.

Initial release

2023

2010

2001

2010

Current release

8.6, January 2023

2.0 SPS07 (April 4, 2023), April 2023

3.5.1, February 2023

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

Elastic License

commercial

Open Source

GPL version 2, commercial licence available

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

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

C++

Java, C++

Server operating systems

server-less

All OS with a Java VM

Appliance or cloud-service

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
OS X

for development

Data scheme

schema-free

Flexible type definitions. Once a type is defined, it is persistent

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.

Secondary indexes

yes

All search fields are automatically indexed

yes

full-text index on all search fields

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

SQL-like query language

yes

SQL-like query language (SphinxQL)

yes

only a subset of SQL 99

APIs and other access methods

Java API
RESTful HTTP/JSON API

JDBC
ODBC

Proprietary protocol

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

Bun
C
C++
Go
JavaScript (Node.js)
Python
Rust

.Net
Groovy
Community Contributed Clients
Java
JavaScript
Perl
PHP
Python
Ruby

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

yes

SQLScript, R

Java

Triggers

yes

by using the 'percolation' feature

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

Sharding

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

ES-Hadoop Connector

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Synchronous doc based replication. Get by ID may show delays up to 1 sec. Configurable write consistency: one, quorum, all

Immediate Consistency

Foreign keys

Referential integrity

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

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

yes

Snapshots and command logging

In-memory capabilities

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

Memcached and Redis integration

yes

User concepts

Access control

yes

Users and roles with access to stored procedures

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