DBMS > GridGain vs. jBASE vs. Memgraph vs. Snowflake vs. Solr

System Properties Comparison GridGain vs. jBASE vs. Memgraph vs. Snowflake vs. Solr

Editorial information provided by DB-Engines

Name

Description

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

A robust multi-value DBMS comprising development tools and middleware

An open source graph database built for real-time streaming and compatible with Neo4j

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

A widely used distributed, scalable search engine based on Apache Lucene

Primary database model

Key-value store
Relational DBMS

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	1.41
Rank	#159	Overall
	#3	Multivalue DBMS

Score	3.02
Rank	#98	Overall
	#8	Graph DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	42.91
Rank	#24	Overall
	#3	Search engines

Website

www.gridgain.com

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-jbase

memgraph.com

www.snowflake.com

solr.apache.org

Technical documentation

www.gridgain.com/docs/index.html

docs.rocketsoftware.com/bundle?labelkey=jbase_5.9

memgraph.com/docs

docs.snowflake.net/manuals/index.html

solr.apache.org/resources.html

Social network pages

Developer

GridGain Systems, Inc.

Rocket Software (formerly Zumasys)

Memgraph Ltd

Snowflake Computing Inc.

Apache Software Foundation

Initial release

2007

1991

2017

2014

2006

Current release

GridGain 8.5.1

5.7

9.6.0, April 2024

License

Commercial or Open Source

commercial

Open Source

BSL 1.1; commercial license for enterprise edition available

commercial

Open Source

Apache Version 2

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++, .Net

C and C++

Java

Server operating systems

Linux
OS X
Solaris
Windows

AIX
Linux
Windows

Linux

hosted

All OS with a Java VM

runs as a servlet in servlet container (e.g. Tomcat, Jetty is included)

Data scheme

yes

schema-free

schema-free and schema-optional

yes

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

yes

Dynamic Fields enables on-the-fly addition of new fields

Typing

predefined data types such as float or date

yes

optional

yes

supports customizable data types and automatic typing

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 search fields are automatically indexed

SQL

Support of SQL

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

Embedded SQL for jBASE in BASIC

yes

Solr Parallel SQL Interface

APIs and other access methods

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

JDBC
ODBC
Proprietary protocol
RESTful HTTP API
SOAP-based API

Bolt protocol
Cypher query language

CLI Client
JDBC
ODBC

Java API
RESTful HTTP/JSON API

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

.Net
Basic
Jabbascript
Java

.Net
C
C++
Elixir
Go
Haskell
Java
JavaScript
PHP
Python
Ruby
Scala

JavaScript (Node.js)
Python

.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

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

yes

user defined functions

Java plugins

Triggers

yes (cache interceptors and events)

yes

similar concept for controling cloud resources

yes

User configurable commands triggered on index changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

dynamic graph partitioning

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

Multi-source replication using RAFT

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

spark-solr: github.com/lucidworks/spark-solr and streaming expressions to reduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Transaction concepts

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

ACID

with snapshot isolation

ACID

optimistic locking

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

Durability

Support for making data persistent

yes

with periodic snapshot and write-ahead logging (WAL) of changes

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

Security Hooks for custom implementations

Access rights can be defined down to the item level

Users, roles and permissions

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

yes

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

Graph algorithms in bioinformatics Social network analysis Cryptocurrency network...
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Licensing and pricing models

You can check out our pricing model and licenses on the company website .
» more

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