DBMS > GridGain vs. Microsoft Azure Cosmos DB vs. ScyllaDB vs. TigerGraph

System Properties Comparison GridGain vs. Microsoft Azure Cosmos DB vs. ScyllaDB vs. TigerGraph

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Editorial information provided by DB-Engines

Name

Description

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

Globally distributed, horizontally scalable, multi-model database service

Cassandra and DynamoDB compatible wide column store

A complete, distributed, parallel graph computing platform supporting web-scale data analytics in real-time

Primary database model

Key-value store
Relational DBMS

Document store
Graph DBMS
Key-value store
Wide column store

Wide column store

Graph DBMS

Secondary database models

Spatial DBMS

Key-value store

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

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

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	4.08
Rank	#76	Overall
	#5	Wide column stores

Score	1.80
Rank	#138	Overall
	#13	Graph DBMS

Website

www.gridgain.com

azure.microsoft.com/services/cosmos-db

www.scylladb.com

www.tigergraph.com

Technical documentation

www.gridgain.com/docs/index.html

learn.microsoft.com/azure/cosmos-db

docs.scylladb.com

docs.tigergraph.com

Developer

GridGain Systems, Inc.

Microsoft

ScyllaDB

Initial release

2007

2014

2015

2017

Current release

GridGain 8.5.1

ScyllaDB Open Source 5.4.1, January 2024

License

Commercial or Open Source

commercial

Open Source

Open Source (AGPL), commercial license available

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.

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Implementation language

Java, C++, .Net

C++

Server operating systems

Linux
OS X
Solaris
Windows

hosted

Linux

Data scheme

yes

schema-free

yes

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

cluster global secondary indices

SQL

Support of SQL

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

SQL-like query language

SQL-like DML and DDL statements (CQL)

SQL-like query language (GSQL)

APIs and other access methods

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

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

Proprietary protocol (CQL)

compatible with CQL (Cassandra Query Language, an SQL-like language)
RESTful HTTP API (DynamoDB compatible)
Thrift

GSQL (TigerGraph Query Language)
Kafka
RESTful HTTP/JSON API

Supported programming languages

C#
C++
Java
PHP
Python
Ruby
Scala

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

For CQL interface: C#, C++, Clojure, Erlang, Go, Haskell, Java, JavaScript, Node.js, Perl, PHP, Python, Ruby, Rust, Scala
For DynamoDB interface: .Net, ColdFusion, Erlang, Groovy, Java, JavaScript, Perl, PHP, Python, Ruby

C++
Java

Server-side scripts

Stored procedures

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

JavaScript

yes, Lua

yes

Triggers

yes (cache interceptors and events)

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes (replicated cache)

yes

Implicit feature of the cloud service

selectable replication factor

Representation of geographical distribution of servers is possible

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Eventual Consistency
Tunable Consistency

can be individually decided for each write operation

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Atomicity and isolation are supported for single operations

ACID

Concurrency

Support for concurrent manipulation of data

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

in-memory tables

User concepts

Access control

Security Hooks for custom implementations

Access rights can be defined down to the item level

Access rights for users can be defined per object

Role-based access control

More information provided by the system vendor

Specific characteristics

ScyllaDB is engineered to deliver predictable performance at scale. It’s adopted...
» more

Competitive advantages

Highly-performant (efficiently utilizes full resources of a node and network; millions...
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Typical application scenarios

ScyllaDB is ideal for applications that require high throughput and low latency at...
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Key customers

Discord, Epic Games, Expedia, Zillow, Comcast, Disney+ Hotstar, Samsung, ShareChat,...
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Market metrics

ScyllaDB typically offers ~75% total cost of ownership savings, with ~5X higher throughput...
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Licensing and pricing models

ScyllaDB Open Source - free open source software (AGPL) ScyllaDB Enterprise - subscription-based...
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