DBMS > Apache Impala vs. Hyprcubd vs. JanusGraph vs. LeanXcale vs. SiteWhere

System Properties Comparison Apache Impala vs. Hyprcubd vs. JanusGraph vs. LeanXcale vs. SiteWhere

Editorial information provided by DB-Engines

Name

Hyprcubd seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.

Description

Analytic DBMS for Hadoop

Serverless Time Series DBMS

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

A highly scalable full ACID SQL database with fast NoSQL data ingestion and GIS capabilities

M2M integration platform for persisting/querying time series data

Primary database model

Relational DBMS

Time Series DBMS

Graph DBMS

Key-value store
Relational DBMS

Time Series DBMS

Secondary database models

Document store

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	0.29
Rank	#291	Overall
	#41	Key-value stores
	#132	Relational DBMS

Score	0.06
Rank	#356	Overall
	#35	Time Series DBMS

Website

impala.apache.org

hyprcubd.com (offline)

janusgraph.org

www.leanxcale.com

github.com/sitewhere/sitewhere

Technical documentation

impala.apache.org/impala-docs.html

docs.janusgraph.org

sitewhere1.sitewhere.io/index.html

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Hyprcubd, Inc.

Linux Foundation; originally developed as Titan by Aurelius

LeanXcale

SiteWhere

Initial release

2013

2017

2015

2010

Current release

4.1.0, June 2022

0.6.3, February 2023

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache 2.0

commercial

Open Source

Common Public Attribution License Version 1.0

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++

Java

Server operating systems

Linux

hosted

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Data scheme

yes

predefined scheme

Typing

predefined data types such as float or date

yes

time, int, uint, float, string

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

SQL-like query language

yes

through Apache Derby

APIs and other access methods

JDBC
ODBC

gRPC (https)

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
Kafka Connector
ODBC
proprietary key/value interface
Spark Connector

HTTP REST

Supported programming languages

All languages supporting JDBC/ODBC

Clojure
Java
Python

C
Java
Scala

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

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, groups and roles

based on Apache Sentry and Kerberos

token access

User authentification and security via Rexster Graph Server

Users with fine-grained authorization concept

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More resources

Recent citations in the news

Apache Impala 4 Supports Operator Multi-Threading
29 July 2021, iProgrammer

Cloudera Bringing Impala to AWS Cloud
28 November 2017, Datanami

Apache Impala becomes Top-Level Project
28 November 2017, SDTimes.com

Apache Doris just 'graduated': Why care about this SQL data warehouse
24 June 2022, InfoWorld

Hudi: Uber Engineering’s Incremental Processing Framework on Apache Hadoop
12 March 2017, Uber

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JanusGraph Picks Up Where TitanDB Left Off
13 January 2017, Datanami

Database Deep Dives: JanusGraph
8 August 2019, ibm.com

From graph db to graph embedding. In 7 simple steps. | by Andy Greatorex
30 July 2020, Towards Data Science

Compose for JanusGraph arrives on Bluemix
15 September 2017, ibm.com

Nordstrom Builds Flexible Backend Ops with Kubernetes, Spark and JanusGraph
3 October 2019, The New Stack

provided by Google News

SiteWhere: An open platform for connected devices
11 July 2017, Open Source For You

Ten Popular IoT Platforms You Should be Aware of
27 March 2023, Open Source For You

11 Best Open source IoT Platforms To Develop Smart Projects
9 March 2023, H2S Media

provided by Google News

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