DBMS > HBase vs. JaguarDB vs. Manticore Search vs. Snowflake vs. TerarkDB

System Properties Comparison HBase vs. JaguarDB vs. Manticore Search vs. Snowflake vs. TerarkDB

Editorial information provided by DB-Engines

Name

Description

Wide-column store based on Apache Hadoop and on concepts of BigTable

Performant, highly scalable DBMS for AI and IoT applications

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

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

A key-value store forked from RocksDB with advanced compression algorithms. It can be used standalone or as a storage engine for MySQL and MongoDB

Primary database model

Wide column store

Key-value store
Vector DBMS

Search engine

Relational DBMS

Key-value store

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.00
Rank	#383	Overall
	#60	Key-value stores

Website

github.com/bytedance/terarkdb

Technical documentation

hbase.apache.org/book.html

www.jaguardb.com/support.html

manual.manticoresearch.com

docs.snowflake.net/manuals/index.html

bytedance.larkoffice.com/docs/doccnZmYFqHBm06BbvYgjsHHcKc

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

DataJaguar, Inc.

Manticore Software

Snowflake Computing Inc.

ByteDance, originally Terark

Initial release

2008

2015

2017

2014

2016

Current release

2.3.4, January 2021

3.3 July 2023

6.0, February 2023

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

GPL V3.0

Open Source

GPL version 2

commercial

restricted open source version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

the server part. Clients available in other languages

C++

Server operating systems

Linux
Unix
Windows

using Cygwin

Linux

FreeBSD
Linux
macOS
Windows

hosted

Data scheme

schema-free, schema definition possible

yes

Fixed schema

yes

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

schema-free

Typing

predefined data types such as float or date

options to bring your own types, AVRO

yes

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

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

SQL

Support of SQL

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

SQL-like query language

yes

APIs and other access methods

Java API
RESTful HTTP API
Thrift

JDBC
ODBC

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

CLI Client
JDBC
ODBC

C++ API
Java API

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

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

JavaScript (Node.js)
Python

C++
Java

Server-side scripts

Stored procedures

yes

Coprocessors in Java

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

Synchronous replication based on Galera library

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Single row ACID (across millions of columns)

yes

isolated transactions for atomic changes and binary logging for safe 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 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

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

rights management via user accounts

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

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