DBMS > GridGain vs. Hive vs. LevelDB vs. Microsoft Azure Cosmos DB vs. Percona Server for MongoDB

System Properties Comparison GridGain vs. Hive vs. LevelDB vs. Microsoft Azure Cosmos DB vs. Percona Server for MongoDB

Editorial information provided by DB-Engines

Name

Description

GridGain is an in-memory computing platform, built on Apache Ignite

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Globally distributed, horizontally scalable, multi-model database service

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Primary database model

Key-value store
Relational DBMS

Relational DBMS

Key-value store

Document store
Graph DBMS
Key-value store
Wide column store

Document store

Secondary database models

Spatial DBMS

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

Score	1.47
Rank	#154	Overall
	#26	Key-value stores
	#72	Relational DBMS

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	2.35
Rank	#111	Overall
	#19	Key-value stores

Score	29.04
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	0.52
Rank	#254	Overall
	#39	Document stores

Website

www.gridgain.com

hive.apache.org

github.com/google/leveldb

azure.microsoft.com/services/cosmos-db

www.percona.com/mongodb/software/percona-server-for-mongodb

Technical documentation

www.gridgain.com/docs/index.html

cwiki.apache.org/confluence/display/Hive/Home

github.com/google/leveldb/blob/main/doc/index.md

learn.microsoft.com/azure/cosmos-db

docs.percona.com/percona-distribution-for-mongodb

Developer

GridGain Systems, Inc.

Apache Software Foundation

initially developed by Facebook

Google

Microsoft

Percona

Initial release

2007

2012

2011

2014

2015

Current release

GridGain 8.5.1

3.1.3, April 2022

1.23, February 2021

3.4.10-2.10, November 2017

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

Open Source

BSD

commercial

Open Source

GPL Version 2

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++, .Net

Java

C++

Server operating systems

Linux
OS X
Solaris
Windows

All OS with a Java VM

Illumos
Linux
OS X
Windows

hosted

Linux

Data scheme

yes

schema-free

Typing

predefined data types such as float or date

yes

JSON 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.

yes

Secondary indexes

yes

All properties auto-indexed by default

yes

SQL

Support of SQL

ANSI-99 for query and DML statements, subset of DDL

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

JDBC
ODBC
Thrift

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

proprietary protocol using JSON

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C++
Java
PHP
Python

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

Server-side scripts

Stored procedures

yes (compute grid and cache interceptors can be used instead)

yes

user defined functions and integration of map-reduce

JavaScript

Triggers

yes (cache interceptors and events)

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

selectable replication factor

none

yes

Implicit feature of the cloud service

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

yes

query execution via MapReduce

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

In-memory capabilities

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

yes

via In-Memory Engine

User concepts

Access control

Security Hooks for custom implementations

Access rights for users, groups and roles

Access rights can be defined down to the item level

Access rights for users and roles

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.