DBMS > atoti vs. BoltDB vs. GridGain vs. searchxml vs. Tkrzw

System Properties Comparison atoti vs. BoltDB vs. GridGain vs. searchxml vs. Tkrzw

Editorial information provided by DB-Engines

Name

Description

An in-memory DBMS combining transactional and analytical processing to handle the aggregation of ever-changing data.

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

DBMS for structured and unstructured content wrapped with an application server

A concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto Cabinet

Primary database model

Object oriented DBMS

Key-value store

Key-value store
Relational DBMS

Native XML DBMS
Search engine

Key-value store

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

Score	0.61
Rank	#243	Overall
	#10	Object oriented DBMS

Score	0.80
Rank	#215	Overall
	#31	Key-value stores

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	0.03
Rank	#390	Overall
	#7	Native XML DBMS
	#24	Search engines

Score	0.07
Rank	#372	Overall
	#57	Key-value stores

Website

atoti.io

github.com/boltdb/bolt

www.gridgain.com

www.searchxml.net/category/products

dbmx.net/tkrzw

Technical documentation

docs.atoti.io

www.gridgain.com/docs/index.html

www.searchxml.net/support/handouts

Developer

ActiveViam

GridGain Systems, Inc.

informationpartners gmbh

Mikio Hirabayashi

Initial release

2013

2007

2015

2020

Current release

GridGain 8.5.1

1.0

0.9.3, August 2020

License

Commercial or Open Source

commercial

free versions available

Open Source

MIT License

commercial

Open Source

Apache Version 2.0

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

Java

Java, C++, .Net

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux
OS X
Solaris
Windows

Windows

Linux
macOS

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

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

SQL

Support of SQL

Multidimensional Expressions (MDX)

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

APIs and other access methods

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

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

C++

most other programming languages supported via APIs

C++
Java
Python
Ruby

Server-side scripts

Stored procedures

Python

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

yes

on the application server

Triggers

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding, horizontal partitioning

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes (replicated cache)

yes

sychronisation to multiple collections

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

yes

ACID

multiple readers, single writer

Concurrency

Support for concurrent manipulation of data

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

using specific database classes

User concepts

Access control

Security Hooks for custom implementations

Domain, group and role-based access control at the document level and for application services

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