DBMS > Apache Impala vs. FatDB vs. H2GIS vs. Splice Machine vs. TinkerGraph

System Properties Comparison Apache Impala vs. FatDB vs. H2GIS vs. Splice Machine vs. TinkerGraph

Editorial information provided by DB-Engines

Name

FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.

Description

Analytic DBMS for Hadoop

A .NET NoSQL DBMS that can integrate with and extend SQL Server.

Spatial extension of H2

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

Relational DBMS

Document store
Key-value store

Spatial DBMS

Relational DBMS

Graph DBMS

Secondary database models

Document store

Relational DBMS

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

Score	13.77
Rank	#40	Overall
	#24	Relational DBMS

Score	0.00
Rank	#383	Overall
	#7	Spatial DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Score	0.08
Rank	#348	Overall
	#35	Graph DBMS

Website

impala.apache.org

www.h2gis.org

splicemachine.com

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

impala.apache.org/impala-docs.html

www.h2gis.org/docs/home

splicemachine.com/how-it-works

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

FatCloud

CNRS

Splice Machine

Initial release

2013

2012

2013

2014

2009

Current release

4.1.0, June 2022

3.1, March 2021

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

LGPL 3.0

Open Source

AGPL 3.0, commercial license available

Open Source

Apache 2.0

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++

Java

Server operating systems

Linux

Windows

Linux
OS X
Solaris
Windows

Data scheme

yes

schema-free

yes

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.

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

Via inetgration in SQL Server

yes

APIs and other access methods

JDBC
ODBC

.NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings

JDBC
Native Spark Datasource
ODBC

TinkerPop 3

Supported programming languages

All languages supporting JDBC/ODBC

Java

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Groovy
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

via applications

yes

based on H2

yes

Java

Triggers

yes

via applications

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

based on H2

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

yes

Yes, via Full Spark Integration

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Eventual Consistency
Immediate Consistency

Immediate Consistency

none

Foreign keys

Referential integrity

yes

Relationships in graphs

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

Durability

Support for making data persistent

yes

optional

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

Can implement custom security layer via applications

yes

based on H2

Access rights for users, groups and roles according to SQL-standard

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More resources

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