DBMS > AgensGraph vs. Microsoft Azure Synapse Analytics vs. NCache vs. RocksDB vs. Splunk

System Properties Comparison AgensGraph vs. Microsoft Azure Synapse Analytics vs. NCache vs. RocksDB vs. Splunk

Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

Open-Source and Enterprise in-memory Key-Value Store

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

Analytics Platform for Big Data

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

Key-value store

Search engine

Secondary database models

Document store
Search engine

Using distributed Lucene

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

Score	0.23
Rank	#315	Overall
	#26	Graph DBMS
	#140	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	0.96
Rank	#195	Overall
	#29	Key-value stores

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	89.10
Rank	#14	Overall
	#2	Search engines

Website

bitnine.net/agensgraph

azure.microsoft.com/services/synapse-analytics

www.alachisoft.com/ncache

rocksdb.org

www.splunk.com

Technical documentation

bitnine.net/documentation

docs.microsoft.com/azure/synapse-analytics

www.alachisoft.com/resources/docs

github.com/facebook/rocksdb/wiki

docs.splunk.com/Documentation/Splunk

Developer

Bitnine Global Inc.

Microsoft

Alachisoft

Facebook, Inc.

Splunk Inc.

Initial release

2016

2005

2013

2003

Current release

2.1, December 2018

5.3.3, April 2024

9.2.1, May 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

Open Source

Enterprise Edition available

Open Source

BSD

commercial

Limited free edition and free developer edition available

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

C++

C#, .NET, .NET Core, Java

C++

Server operating systems

Linux
OS X
Windows

hosted

Linux
Windows

Linux

Linux
OS X
Solaris
Windows

Data scheme

depending on used data model

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

partial

Supported data types are Lists, Queues, Hashsets, Dictionary and Counter

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

yes

SQL-like query syntax and LINQ for searching the cache. Cache Synchronization with SQL Server using SQL dependency.

Splunk Search Processing Language for search commands

APIs and other access methods

Cypher Query Language
JDBC

ADO.NET
JDBC
ODBC

IDistributedCache
JCache
LINQ
Proprietary native API

C++ API
Java API

HTTP REST

Supported programming languages

C
Java
JavaScript
Python

C#
Java
PHP

.Net
.Net Core
C#
Java
JavaScript (Node.js)
Python
Scala

C
C++
Go
Java
Perl
Python
Ruby

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

yes

Transact SQL

support for stored procedures with SQL-Server CLR

yes

Triggers

yes

Notifications

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

Sharding, horizontal partitioning

yes

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

yes, with selectable consistency level

yes

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency
Strong Eventual Consistency over WAN with Conflict Resolution using Bridge Topology

Eventual Consistency

Foreign keys

Referential integrity

yes

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

Transaction concepts

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

ACID

optimistic locking and pessimistic locking

yes

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

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

User concepts

Access control

fine grained access rights according to SQL-standard

yes

Authentication to access the cache via Active Directory/LDAP (possible roles: user, administrator)

Access rights for users and roles

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Key customers

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Market metrics

Market Leader in .NET Distributed Caching since 2005.
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Licensing and pricing models

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