DBMS > Apache Impala vs. BoltDB vs. EventStoreDB vs. Graph Engine vs. STSdb

System Properties Comparison Apache Impala vs. BoltDB vs. EventStoreDB vs. Graph Engine vs. STSdb

Editorial information provided by DB-Engines

Name

Description

Analytic DBMS for Hadoop

Industrial-strength, open-source database solution built from the ground up for event sourcing.

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

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Relational DBMS

Key-value store

Event Store

Graph DBMS
Key-value store

Key-value store

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	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	1.10
Rank	#179	Overall
	#1	Event Stores

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

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

impala.apache.org

github.com/boltdb/bolt

www.eventstore.com

www.graphengine.io

github.com/STSSoft/STSdb4

Technical documentation

impala.apache.org/impala-docs.html

developers.eventstore.com

www.graphengine.io/docs/manual

Developer

Apache Software Foundation

Apache top-level project, originally developed by Cloudera

Event Store Limited

Microsoft

STS Soft SC

Initial release

2013

2012

2010

2011

Current release

4.1.0, June 2022

21.2, February 2021

4.0.8, September 2015

License

Commercial or Open Source

Open Source

Apache Version 2

Open Source

MIT License

Open Source

MIT License

Open Source

GPLv2, commercial license 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++

.NET and C

Server operating systems

Linux

BSD
Linux
OS X
Solaris
Windows

Linux
Windows

.NET

Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

primitive types and user defined types (classes)

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

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

.NET Client API

Supported programming languages

All languages supporting JDBC/ODBC

C#
C++
F#
Visual Basic

C#
Java

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

none

Foreign keys

Referential integrity

Transaction concepts

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

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

Access rights for users, groups and roles

based on Apache Sentry and Kerberos

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More resources

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