DBMS > Apache IoTDB vs. Graph Engine vs. InterSystems Caché vs. RocksDB

System Properties Comparison Apache IoTDB vs. Graph Engine vs. InterSystems Caché vs. RocksDB

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Editorial information provided by DB-Engines

Name

Caché is a deprecated database engine which is substituted with InterSystems IRIS. It therefore is removed from the DB-Engines Ranking.

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

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

A multi-model DBMS and application server

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

Primary database model

Time Series DBMS

Graph DBMS
Key-value store

Key-value store
Object oriented DBMS
Relational DBMS

Key-value store

Secondary database models

Document store

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

Score	1.18
Rank	#173	Overall
	#15	Time Series DBMS

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

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

Website

iotdb.apache.org

www.graphengine.io

www.intersystems.com/products/cache

rocksdb.org

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

www.graphengine.io/docs/manual

docs.intersystems.com

github.com/facebook/rocksdb/wiki

Developer

Apache Software Foundation

Microsoft

InterSystems

Facebook, Inc.

Initial release

2018

2010

1997

2013

Current release

1.1.0, April 2023

2018.1.4, May 2020

8.11.4, April 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

Open Source

MIT License

commercial

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

Java

.NET and C

C++

Server operating systems

All OS with a Java VM (>= 1.8)

.NET

AIX
HP Open VMS
HP-UX
Linux
OS X
Solaris
Windows

Linux

Data scheme

yes

depending on used data model

schema-free

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

Secondary indexes

yes

SQL

Support of SQL

SQL-like query language

yes

APIs and other access methods

JDBC
Native API

RESTful HTTP API

.NET Client API
JDBC
ODBC
RESTful HTTP API

C++ API
Java API

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

C#
C++
F#
Visual Basic

C#
C++
Java

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

horizontal partitioning

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

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

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

yes

Access rights for users, groups and roles

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