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

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

Editorial information provided by DB-Engines

Name

Description

An embedded key-value store for Go.

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

A distributed, high available RDBMS compatible with Oracle and MySQL

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

Primary database model

Key-value store

Time Series DBMS

Event Store
Time Series DBMS

Relational DBMS

Key-value store

Secondary database models

Document store
Wide column store

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

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

Score	0.51
Rank	#255	Overall
	#21	Time Series DBMS

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

Score	1.66
Rank	#147	Overall
	#68	Relational DBMS

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

Website

github.com/boltdb/bolt

github.com/spotify/heroic

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

en.oceanbase.com

rocksdb.org

Technical documentation

spotify.github.io/heroic

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

en.oceanbase.com/docs/oceanbase-database

github.com/facebook/rocksdb/wiki

Developer

Spotify

IBM

OceanBase

previously Alibaba and Ant Group

Facebook, Inc.

Initial release

2013

2014

2017

2010

2013

Current release

2.0

4.3.0, April 2024

9.2.1, May 2024

License

Commercial or Open Source

Open Source

MIT License

Open Source

Apache 2.0

commercial

free developer edition available

Open Source

Commercial license 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

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

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

yes

SQL

Support of SQL

yes

through the embedded Spark runtime

yes

APIs and other access methods

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

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Proprietary native API
Table 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

Ada

in MySQL-compatible model
C

in Oracle- and MySQL- compatible models
C++

in Oracle- and MySQL- compatible models
D

in MySQL-compatible model
Delphi

in MySQL-compatible model
Eiffel

in MySQL-compatible model
Erlang

in MySQL-compatible model
Haskell

in MySQL-compatible model
Java

in Oracle- and MySQL- compatible models
JavaScript (Node.js)

in MySQL-compatible model
Objective-C

in MySQL-compatible model
OCaml

in MySQL-compatible model
Perl

in MySQL-compatible model
PHP

in MySQL-compatible model
Python

in MySQL-compatible model
Ruby

in MySQL-compatible model
Scheme

in MySQL-compatible model
Tcl

in MySQL-compatible model

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes

PL/SQL in oracle-compatible mode, MySQL Stored Procedure in mysql-compatible mode

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

horizontal partitioning (by hash, key, range, range columns, list, and list columns)

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

yes

Active-active shard replication

Multi-source replication using Paxos

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

none

Eventual Consistency
Immediate Consistency

Eventual Consistency

Immediate 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

fine grained access rights according to SQL-standard

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

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