DBMS > Google Cloud Spanner vs. HarperDB vs. ObjectBox vs. Snowflake vs. Splunk

System Properties Comparison Google Cloud Spanner vs. HarperDB vs. ObjectBox vs. Snowflake vs. Splunk

Editorial information provided by DB-Engines

Name

Description

A horizontally scalable, globally consistent, relational database service. It is the externalization of the core Google database that runs the biggest aspects of Google, like Ads and Google Play.

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.

Lightweight, fast on-device database for IoT, Mobile and Embedded devices, persisting and synchronising objects and vectors

Cloud-based data warehousing service for structured and semi-structured data

Analytics Platform for Big Data

Primary database model

Relational DBMS

Document store

Object oriented DBMS
Vector DBMS

Relational DBMS

Search engine

Secondary database models

Time Series DBMS

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

Score	2.69
Rank	#101	Overall
	#51	Relational DBMS

Score	0.55
Rank	#243	Overall
	#38	Document stores

Score	1.08
Rank	#179	Overall
	#6	Object oriented DBMS
	#9	Vector DBMS

Score	133.72
Rank	#7	Overall
	#5	Relational DBMS

Score	93.02
Rank	#13	Overall
	#2	Search engines

Website

cloud.google.com/spanner

www.harperdb.io

github.com/objectbox
objectbox.io

www.snowflake.com

www.splunk.com

Technical documentation

cloud.google.com/spanner/docs

docs.harperdb.io/docs

docs.objectbox.io

docs.snowflake.net/manuals/index.html

docs.splunk.com/Documentation/Splunk

Developer

Google

HarperDB

ObjectBox Limited

Snowflake Computing Inc.

Splunk Inc.

Initial release

2017

2014

2003

Current release

3.1, August 2021

4.0 (May 2024)

License

Commercial or Open Source

commercial

free community edition available

Bindings are released under Apache 2.0

Apache License 2.0

commercial

Limited free edition and free developer edition available

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

C and C++

Server operating systems

hosted

Linux
OS X

Android
Any POSIX system
Docker
iOS
Linux
macOS
QNX
Windows

hosted

Linux
OS X
Solaris
Windows

Data scheme

yes

dynamic schema

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

yes

JSON data types

yes, plus "flex" map-like types

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

SQL

Support of SQL

yes

Query statements complying to ANSI 2011

SQL-like data manipulation statements

yes

Splunk Search Processing Language for search commands

APIs and other access methods

gRPC (using protocol buffers) API
JDBC

At present, JDBC supports read-only queries. No support for DDL or DML statements.
RESTful HTTP API

JDBC
ODBC
React Hooks
RESTful HTTP/JSON API
WebSocket

Proprietary native API

CLI Client
JDBC
ODBC

HTTP REST

Supported programming languages

Go
Java
JavaScript (Node.js)
Python

.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

C
C++
Dart (Flutter)
Go
Java
Kotlin
Python
Swift

JavaScript (Node.js)
Python

C#
Java
JavaScript
PHP
Python
Ruby

Server-side scripts

Stored procedures

Custom Functions

since release 3.1

user defined functions

yes

Triggers

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

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

none

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication with 3 replicas for regional instances.

yes

the nodes on which a table resides can be defined

Data sync between devices allowing occasional connected databases to work completely offline

yes

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

using Google Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

by using interleaved tables, this features focuses more on performance improvements than on referential integrity

yes

Transaction concepts

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

ACID

Strict serializable isolation

Atomic execution of specific operations

ACID

A 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searching

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 rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

Access rights for users and roles

yes

Users with fine-grained authorization concept, user roles and pluggable authentication

Access rights for users and roles

More information provided by the system vendor

News

MongoDB Realm & Device Sync alternatives – ObjectBox
17 September 2024

Local AI – what it is and why we need it
11 September 2024

First on-device Vector Database (aka Semantic Index) for iOS
24 July 2024

Retrieval Augmented Generation (RAG) with vector databases: Expanding AI Capabilities
18 June 2024

The on-device Vector Database for Android and Java
29 May 2024

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