DBMS > BigObject vs. Manticore Search vs. TimescaleDB vs. Transwarp KunDB

System Properties Comparison BigObject vs. Manticore Search vs. TimescaleDB vs. Transwarp KunDB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Multi-storage database for search, including full-text search.

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

OLTP DBMS based on a distributed architecture and highly compatible with MySQL and Oracle

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Search engine

Time Series DBMS

Relational DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

Relational DBMS

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

Score	0.13
Rank	#329	Overall
	#147	Relational DBMS

Score	0.23
Rank	#301	Overall
	#21	Search engines

Score	4.06
Rank	#73	Overall
	#5	Time Series DBMS

Score	0.04
Rank	#362	Overall
	#154	Relational DBMS

Website

bigobject.io

manticoresearch.com

www.timescale.com

www.transwarp.cn/en/product/kundb

Technical documentation

docs.bigobject.io

manual.manticoresearch.com

docs.timescale.com

Developer

BigObject, Inc.

Manticore Software

Timescale

Transwarp

Initial release

2015

2017

Current release

6.0, February 2023

2.15.0, May 2024

License

Commercial or Open Source

commercial

free community edition available

Open Source

GPL version 2

Open Source

Apache 2.0

commercial

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

FreeBSD
Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

yes

Fixed schema

yes

Typing

predefined data types such as float or date

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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

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.

Can index from XML

yes

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

yes

full PostgreSQL SQL syntax

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

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

Supported programming languages

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Lua

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

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

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

yes, across time and space (hash partitioning) attributes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Synchronous replication based on Galera library

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

none

Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Transaction concepts

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

yes

isolated transactions for atomic changes and binary logging for safe writes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

yes

Durability

Support for making data persistent

yes

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

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

fine grained access rights according to SQL-standard

yes

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

Comparing Meilisearch and Manticore Search Using Key Benchmarks
2 May 2023, hackernoon.com

Manticore is a Faster Alternative to Elasticsearch in C++
25 July 2022, hackernoon.com

Integrating Manticore Search with Apache Superset
8 August 2023, hackernoon.com

Highlighting in Search Results
24 May 2020, hackernoon.com

40 Stories To Learn About Elasticsearch
27 April 2023, hackernoon.com

provided by Google News

General availability: Latest version of the TimeScaleDB extension on Azure Database for PostgreSQL - Flexible Server
8 May 2024, Microsoft

Timescale Acquires PopSQL to Bring a Modern, Collaborative SQL GUI to PostgreSQL Developers
4 April 2024, PR Newswire

TimescaleDB Is a Vector Database Now, Too
25 September 2023, Datanami

PostgreSQL is Now Faster than Pinecone, 75% Cheaper, with New Open Source Extensions
11 June 2024, PR Newswire

Understanding Hyperfunctions in TimescaleDB
11 August 2021, CDOTrends

provided by Google News

Share this page