DBMS > BigObject vs. HarperDB vs. InterSystems IRIS vs. Manticore Search vs. Snowflake

System Properties Comparison BigObject vs. HarperDB vs. InterSystems IRIS vs. Manticore Search vs. Snowflake

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for real-time computations and queries

Ultra-low latency distributed database with an intuitive REST API supporting NoSQL and SQL (including joins). Deployment of functions and databases simultaneously with a consolidated node-level architecture.

A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalability

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

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

Primary database model

Relational DBMS

a hierachical model (tree) can be imposed

Document store

Document store
Key-value store
Object oriented DBMS
Relational DBMS

Search engine

Relational DBMS

Secondary database models

Time Series DBMS

using the Manticore Columnar Library

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

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	0.55
Rank	#248	Overall
	#38	Document stores

Score	4.05
Rank	#83	Overall
	#14	Document stores
	#10	Key-value stores
	#1	Object oriented DBMS
	#45	Relational DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Website

bigobject.io

www.harperdb.io

www.intersystems.com/products/intersystems-iris

manticoresearch.com

www.snowflake.com

Technical documentation

docs.bigobject.io

docs.harperdb.io/docs

docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls

manual.manticoresearch.com

docs.snowflake.net/manuals/index.html

Developer

BigObject, Inc.

HarperDB

InterSystems

Manticore Software

Snowflake Computing Inc.

Initial release

2015

2017

2018

2017

2014

Current release

3.1, August 2021

2023.3, June 2023

6.0, February 2023

License

Commercial or Open Source

commercial

free community edition available

commercial

free community edition available

commercial

Open Source

GPL version 2

commercial

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

Node.js

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)

Linux
OS X

AIX
Linux
macOS
Ubuntu
Windows

FreeBSD
Linux
macOS
Windows

hosted

Data scheme

yes

dynamic schema

depending on used data model

Fixed schema

yes

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

Typing

predefined data types such as float or date

yes

JSON data types

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.

yes

Can index from XML

yes

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like data manipulation statements

yes

SQL-like query language

yes

APIs and other access methods

fluentd
ODBC
RESTful HTTP API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

JDBC
ODBC
RESTful HTTP API

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

CLI Client
JDBC
ODBC

Supported programming languages

.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

.Net
C++
Java
JavaScript (Node.js)
Python

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

Lua

Custom Functions

since release 3.1

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

none

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

yes

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

the nodes on which a table resides can be defined

Source-replica replication

Synchronous replication based on Galera library

yes

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

Atomic execution of specific operations

ACID

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

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 and roles

yes

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

More information provided by the system vendor

Specific characteristics

InterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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