DBMS > Immudb vs. MySQL vs. Sphinx vs. Tigris vs. TimescaleDB

System Properties Comparison Immudb vs. MySQL vs. Sphinx vs. Tigris vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

An open source immutable (append-only) database with cryptographic verification which makes it tamper-resistant and fully auditable.

Widely used open source RDBMS

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

A horizontally scalable, ACID transactional, document database available both as a fully managed cloud service and for deployment on self-managed infrastructure

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

Primary database model

Key-value store

Relational DBMS

Key/Value like access via memcached API

Search engine

Document store
Key-value store
Search engine
Time Series DBMS

Time Series DBMS

Secondary database models

Relational DBMS

Document store
Spatial DBMS

Relational DBMS

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

Score	0.24
Rank	#305	Overall
	#43	Key-value stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.02
Rank	#369	Overall
	#51	Document stores
	#55	Key-value stores
	#24	Search engines
	#38	Time Series DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

github.com/codenotary/immudb
immudb.io

Technical documentation

docs.immudb.io

dev.mysql.com/doc

sphinxsearch.com/docs

www.tigrisdata.com/docs

docs.timescale.com

Developer

Codenotary

Oracle

since 2010, originally MySQL AB, then Sun

Sphinx Technologies Inc.

Tigris Data, Inc.

Timescale

Initial release

2020

1995

2001

2022

2017

Current release

1.2.3, April 2022

8.3.0, January 2024

3.5.1, February 2023

2.13.0, November 2023

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL version 2, commercial licence available

Open Source

Apache Version 2.0

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C and C++

C++

Server operating systems

BSD
Linux
macOS
Solaris
Windows
z/OS

FreeBSD
Linux
OS X
Solaris
Windows

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

yes

SQL

Support of SQL

SQL-like syntax

yes

with proprietary extensions

SQL-like query language (SphinxQL)

yes

full PostgreSQL SQL syntax

APIs and other access methods

gRPC protocol
PostgreSQL wire protocol

ADO.NET
JDBC
ODBC
Proprietary native API

Proprietary protocol

CLI Client
gRPC
RESTful HTTP API

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

Supported programming languages

.Net
Go
Java
JavaScript (Node.js)
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

Go
Java
JavaScript (Node.js)

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes

proprietary syntax

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

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

Sharding

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

yes

Source-replica replication with hot standby and reads on replicas

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

not for MyISAM storage engine

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

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

yes, using FoundationDB

yes

In-memory capabilities

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

yes

User concepts

Access control

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles

fine grained access rights according to SQL-standard

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