DBMS > AnzoGraph DB vs. Brytlyt vs. GridGain vs. RocksDB vs. Splunk

System Properties Comparison AnzoGraph DB vs. Brytlyt vs. GridGain vs. RocksDB vs. Splunk

Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Scalable GPU-accelerated RDBMS for very fast analytic and streaming workloads, leveraging PostgreSQL

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

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

Analytics Platform for Big Data

Primary database model

Graph DBMS
RDF store

Relational DBMS

Key-value store
Relational DBMS

Key-value store

Search engine

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

Score	0.23
Rank	#307	Overall
	#24	Graph DBMS
	#13	RDF stores

Score	0.29
Rank	#288	Overall
	#131	Relational DBMS

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

Score	3.65
Rank	#85	Overall
	#11	Key-value stores

Score	86.45
Rank	#14	Overall
	#2	Search engines

Website

cambridgesemantics.com/anzograph

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

docs.brytlyt.io

www.gridgain.com/docs/index.html

github.com/facebook/rocksdb/wiki

docs.splunk.com/Documentation/Splunk

Developer

Cambridge Semantics

Brytlyt

GridGain Systems, Inc.

Facebook, Inc.

Splunk Inc.

Initial release

2018

2016

2007

2013

2003

Current release

2.3, January 2021

5.0, August 2023

GridGain 8.5.1

9.2.1, May 2024

License

Commercial or Open Source

commercial

free trial version available

commercial

Open Source

BSD

commercial

Limited free edition and free developer edition available

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

C, C++ and CUDA

Java, C++, .Net

C++

Server operating systems

Linux

Linux
OS X
Windows

Linux
OS X
Solaris
Windows

Linux

Linux
OS X
Solaris
Windows

Data scheme

Schema-free and OWL/RDFS-schema support

yes

schema-free

yes

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

specific XML-type available, but no XML query functionality.

yes

Secondary indexes

yes

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

yes

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

Splunk Search Processing Language for search commands

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

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

C++ API
Java API

HTTP REST

Supported programming languages

C++
Java
Python

.Net
C
C++
Delphi
Java
Perl
Python
Tcl

C#
C++
Java
PHP
Python
Ruby
Scala

C
C++
Go
Java
Perl
Python
Ruby

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions and aggregates

user defined functions

in PL/pgSQL

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

yes

Triggers

yes

yes (cache interceptors and events)

yes

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Source-replica replication

yes (replicated cache)

yes

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

yes (compute grid and hadoop accelerator)

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Transaction concepts

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

ACID

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

Access rights for users and roles

fine grained access rights according to SQL-standard

Security Hooks for custom implementations

Access rights for users and roles

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