DBMS > GridDB vs. HarperDB vs. Manticore Search vs. RethinkDB

System Properties Comparison GridDB vs. HarperDB vs. Manticore Search vs. RethinkDB

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Editorial information provided by DB-Engines

Name

Description

Scalable in-memory time series database optimized for IoT and Big Data

HarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.

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

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Primary database model

Secondary database models

Key-value store
Relational DBMS

Time Series DBMS

using the Manticore Columnar Library

Spatial DBMS

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

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Score	0.55
Rank	#243	Overall
	#38	Document stores

Score	0.23
Rank	#301	Overall
	#21	Search engines

Score	2.58
Rank	#105	Overall
	#20	Document stores

Website

Technical documentation

docs.griddb.net

docs.harperdb.io/docs

manual.manticoresearch.com

rethinkdb.com/docs

Developer

Toshiba Corporation

HarperDB

Manticore Software

The Linux Foundation

since July 2017

Initial release

2013

2017

2009

Current release

5.1, August 2022

3.1, August 2021

6.0, February 2023

2.4.1, August 2020

License

Commercial or Open Source

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

commercial

free community edition available

Open Source

GPL version 2

Open Source

Apache Version 2

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++

Node.js

C++

Server operating systems

Linux

Linux
OS X

FreeBSD
Linux
macOS
Windows

Linux
OS X
Windows

Data scheme

yes

dynamic schema

Fixed schema

schema-free

Typing

predefined data types such as float or date

yes

numerical, string, blob, geometry, boolean, timestamp

yes

JSON data types

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

yes

string, binary, float, bool, date, geometry

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

Secondary indexes

yes

full-text index on all search fields

yes

SQL

Support of SQL

SQL92, SQL-like TQL (Toshiba Query Language)

SQL-like data manipulation statements

SQL-like query language

APIs and other access methods

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

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

Supported programming languages

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

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

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

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

user defined functions

Triggers

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

A table resides as a whole on one (or more) nodes in a cluster

Sharding

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

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

the nodes on which a table resides can be defined

Synchronous replication based on Galera library

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID at container level

Atomic execution of specific operations

yes

isolated transactions for atomic changes and binary logging for safe writes

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

Durability

Support for making data persistent

yes

yes, using LMDB

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 rights for users can be defined per database

Access rights for users and roles

yes

users and table-level permissions

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More resources

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