DBMS > BoltDB vs. GBase vs. Heroic vs. IBM Db2 Event Store vs. RocksDB

System Properties Comparison BoltDB vs. GBase vs. Heroic vs. IBM Db2 Event Store vs. RocksDB

Editorial information provided by DB-Engines

Name

Description

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Time Series DBMS built at Spotify based on Cassandra or Google Cloud Bigtable, and ElasticSearch

Distributed Event Store optimized for Internet of Things use cases

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

Primary database model

Key-value store

Relational DBMS

Time Series DBMS

Event Store
Time Series DBMS

Key-value store

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

Score	0.74
Rank	#220	Overall
	#31	Key-value stores

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

Score	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

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

Website

github.com/boltdb/bolt

www.gbase.cn

github.com/spotify/heroic

www.ibm.com/products/db2-event-store

rocksdb.org

Technical documentation

spotify.github.io/heroic

www.ibm.com/docs/en/db2-event-store

github.com/facebook/rocksdb/wiki

Developer

General Data Technology Co., Ltd.

Spotify

IBM

Facebook, Inc.

Initial release

2013

2004

2014

2017

2013

Current release

GBase 8a, GBase 8s, GBase 8c

2.0

9.2.1, May 2024

License

Commercial or Open Source

Open Source

MIT License

commercial

Open Source

Apache 2.0

commercial

free developer edition available

Open Source

BSD

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, Python

Java

C and C++

C++

Server operating systems

BSD
Linux
OS X
Solaris
Windows

Linux

Linux, macOS, Windows for the developer addition

Linux

Data scheme

schema-free

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.

yes

Secondary indexes

yes

via Elasticsearch

SQL

Support of SQL

Standard with numerous extensions

yes

through the embedded Spark runtime

APIs and other access methods

ADO.NET
C API
JDBC
ODBC

HQL (Heroic Query Language, a JSON-based language)
HTTP API

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

C++ API
Java API

Supported programming languages

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Active-active shard replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Eventual Consistency
Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared 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

fine grained access rights according to SQL-standard

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