DBMS > Google BigQuery vs. HarperDB vs. InfinityDB vs. RocksDB

System Properties Comparison Google BigQuery vs. HarperDB vs. InfinityDB vs. RocksDB

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service with append-only tables

HarperDB takes the "stack" out of "tech stack" by combining an ultra-fast document-style data store, in-memory cache, real-time message broker, and your application components into a single distributed technology.

A Java embedded Key-Value Store which extends the Java Map interface

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

Primary database model

Relational DBMS

Document store

Key-value store

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

Score	52.67
Rank	#19	Overall
	#13	Relational DBMS

Score	0.55
Rank	#243	Overall
	#38	Document stores

Score	0.00
Rank	#383	Overall
	#59	Key-value stores

Score	2.84
Rank	#97	Overall
	#16	Key-value stores

Website

cloud.google.com/bigquery

www.harperdb.io

boilerbay.com

rocksdb.org

Technical documentation

cloud.google.com/bigquery/docs

docs.harperdb.io/docs

boilerbay.com/infinitydb/manual

github.com/facebook/rocksdb/wiki

Developer

Google

HarperDB

Boiler Bay Inc.

Facebook, Inc.

Initial release

2010

2017

2002

2013

Current release

3.1, August 2021

4.0

9.4.0, June 2024

License

Commercial or Open Source

commercial

free community edition available

commercial

Open Source

BSD

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

Node.js

Java

C++

Server operating systems

hosted

Linux
OS X

All OS with a Java VM

Linux

Data scheme

yes

dynamic schema

yes

nested virtual Java Maps, multi-value, logical â€˜tuple spaceâ€™ runtime Schema upgrade

schema-free

Typing

predefined data types such as float or date

yes

JSON data types

yes

all Java primitives, Date, CLOB, BLOB, huge sparse arrays

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

manual creation possible, using inversions based on multi-value capability

SQL

Support of SQL

yes

SQL-like data manipulation statements

APIs and other access methods

RESTful HTTP/JSON API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Access via java.util.concurrent.ConcurrentNavigableMap Interface
Proprietary API to InfinityDB ItemSpace (boilerbay.com/docs/ItemSpaceDataStructures.htm)

C++ API
Java API

Supported programming languages

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

.Net
C
C#
C++
ColdFusion
D
Dart
Delphi
Erlang
Go
Haskell
Java
JavaScript (Node.js)
Lisp
MatLab
Objective C
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Rust
Scala
Swift

Java

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in JavaScript

Custom Functions

since release 3.1

Triggers

Partitioning methods

Methods for storing different data on different nodes

none

A table resides as a whole on one (or more) nodes in a cluster

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

the nodes on which a table resides can be defined

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

READ-COMMITTED or SERIALIZED

Foreign keys

Referential integrity

manual creation possible, using inversions based on multi-value capability

Transaction concepts

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

Since BigQuery is designed for querying data

Atomic execution of specific operations

ACID

Optimistic locking for transactions; no isolation for bulk loads

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, using LMDB

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 privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

Access rights for users and roles

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