DBMS > OpenTSDB vs. Sequoiadb vs. Snowflake vs. Sphinx vs. TimescaleDB

System Properties Comparison OpenTSDB vs. Sequoiadb vs. Snowflake vs. Sphinx vs. TimescaleDB

Editorial information provided by DB-Engines

Name

Description

Scalable Time Series DBMS based on HBase

NewSQL database with distributed OLTP and SQL

Cloud-based data warehousing service for structured and semi-structured data

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

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

Primary database model

Time Series DBMS

Document store
Relational DBMS

Relational DBMS

Search engine

Time Series DBMS

Secondary database models

Relational DBMS

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

Score	1.68
Rank	#146	Overall
	#12	Time Series DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	5.98
Rank	#56	Overall
	#5	Search engines

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

Technical documentation

opentsdb.net/docs/build/html/index.html

www.sequoiadb.com/en/index.php?m=Files&a=index

docs.snowflake.net/manuals/index.html

sphinxsearch.com/docs

docs.timescale.com

Developer

currently maintained by Yahoo and other contributors

Sequoiadb Ltd.

Snowflake Computing Inc.

Sphinx Technologies Inc.

Timescale

Initial release

2011

2013

2014

2001

2017

Current release

3.5.1, February 2023

2.13.0, November 2023

License

Commercial or Open Source

Open Source

LGPL

Open Source

Server: AGPL; Client: Apache V2

commercial

Open Source

GPL version 2, commercial licence available

Open Source

Apache 2.0

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

C++

Server operating systems

Linux
Windows

Linux

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

numeric data for metrics, strings for tags

yes

oid, date, timestamp, binary, regex

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 query language

yes

SQL-like query language (SphinxQL)

yes

full PostgreSQL SQL syntax

APIs and other access methods

HTTP API
Telnet API

proprietary protocol using JSON

CLI Client
JDBC
ODBC

Proprietary protocol

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

Supported programming languages

Erlang
Go
Java
Python
R
Ruby

.Net
C++
Java
PHP
Python

JavaScript (Node.js)
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

JavaScript

user defined functions

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

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

based on HBase

Sharding

yes

Sharding

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

yes, across time and space (hash partitioning) attributes

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

based on HBase

Source-replica replication

yes

none

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

based on HBase

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Document is locked during a transaction

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.

yes

In-memory capabilities

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

User concepts

Access control

simple password-based access control

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

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