DBMS > Graph Engine vs. Graphite vs. HEAVY.AI vs. Manticore Search vs. RocksDB

System Properties Comparison Graph Engine vs. Graphite vs. HEAVY.AI vs. Manticore Search vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Data logging and graphing tool for time series data

The storage layer (fixed size database) is called Whisper

A high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardware

Multi-storage database for search, including full-text search.

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

Primary database model

Graph DBMS
Key-value store

Secondary database models

Spatial DBMS

Time Series DBMS

using the Manticore Columnar Library

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

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	4.57
Rank	#73	Overall
	#5	Time Series DBMS

Score	1.77
Rank	#141	Overall
	#65	Relational DBMS

Score	0.22
Rank	#312	Overall
	#21	Search engines

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

Website

www.graphengine.io

github.com/graphite-project/graphite-web

github.com/heavyai/heavydb
www.heavy.ai

manticoresearch.com

rocksdb.org

Technical documentation

www.graphengine.io/docs/manual

graphite.readthedocs.io

docs.heavy.ai

manual.manticoresearch.com

github.com/facebook/rocksdb/wiki

Developer

Microsoft

Chris Davis

HEAVY.AI, Inc.

Manticore Software

Facebook, Inc.

Initial release

2010

2006

2016

2017

2013

Current release

5.10, January 2022

6.0, February 2023

9.2.1, May 2024

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache 2.0

Open Source

Apache Version 2; enterprise edition available

Open Source

GPL version 2

Open Source

BSD

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

.NET and C

Python

C++ and CUDA

C++

Server operating systems

.NET

Linux
Unix

Linux

FreeBSD
Linux
macOS
Windows

Linux

Data scheme

yes

Fixed schema

schema-free

Typing

predefined data types such as float or date

yes

Numeric data only

yes

Int, Bigint, Float, Timestamp, Bit, Int array, Bigint array, JSON, Boolean

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.

Can index from XML

Secondary indexes

yes

full-text index on all search fields

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

RESTful HTTP API

HTTP API
Sockets

JDBC
ODBC
Thrift
Vega

Binary API
RESTful HTTP/JSON API
RESTful HTTP/SQL API
SQL over MySQL

C++ API
Java API

Supported programming languages

C#
C++
F#
Visual Basic

JavaScript (Node.js)
Python

All languages supporting JDBC/ODBC/Thrift
Python

Elixir
Go
Java
JavaScript (Node.js)
Perl
PHP
Python

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

Round robin

Sharding

Partitioning is done manually, search queries against distributed index is supported

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

Multi-source replication

Synchronous replication based on Galera library

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

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

isolated transactions for atomic changes and binary logging for safe writes

yes

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

Durability

Support for making data persistent

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

yes

The original contents of fields are not stored in the Manticore index.

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

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