Apache Spark VS SQL Developer

Compare Apache Spark VS SQL Developer and see what are their differences

Rating: 0 reviews
Pricing: Open source

Rating: 0 reviews

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Which is more popular?

Based on our record, Apache Spark seems to be more popular. It has been mentioned 80 times since March 2021.

social mentions: 80 vs 0
Databases popularity: 57% vs 43%
alternatives listed: 118 vs 161

Base details

Website, pricing, platforms and company facts side by side.

	Apache Spark	SQL Developer
Website	spark.apache.org	oracle.com
Pricing	Open source	—
Listed in	Databases Big Data Big Data Analytics Big Data Infrastructure +1	Database Management Databases Database Tools MySQL Tools +1

Features and specs

What each product offers, as listed by its team.

Apache Spark 6 features

SQL Developer 6 features

Speed
Apache Spark processes data in-memory, significantly increasing the processing speed of data tasks compared to traditional disk-based engines.
Ease of Use
Spark offers high-level APIs in Java, Scala, Python, and R, making it accessible to a broad range of developers and data scientists.
Advanced Analytics
Spark supports advanced analytics, including machine learning, graph processing, and real-time streaming, which can be executed in the same application.
Scalability
Spark can handle both small- and large-scale data processing tasks, scaling seamlessly from a single machine to thousands of servers.
Support for Various Data Sources
Spark can integrate with a wide variety of data sources, including HDFS, Apache HBase, Apache Hive, Cassandra, and many others.
Active Community
Spark has a vibrant and active community, providing a wealth of extensions, tools, and support options.

Possible disadvantages

Memory Consumption
Spark's in-memory processing can be resource-intensive, requiring substantial amounts of RAM, which can drive up costs for large-scale deployments.
Complexity in Configuration
To optimize performance, Spark requires careful configuration and tuning, which can be complex and time-consuming.
Learning Curve
Despite its ease of use, mastering the full range of Spark's features and best practices can take considerable time and effort.
Latency for Small Data
For smaller datasets or low-latency requirements, Spark might not be the most efficient choice, as other technologies could offer better performance.
Integration Overhead
Though Spark integrates with many systems, incorporating it into an existing data infrastructure can introduce additional overhead and complexity.
Community Support Variability
While the community is active, the support and quality of third-party libraries and tools can be inconsistent, leading to potential challenges in implementation.

Comprehensive Feature Set
SQL Developer offers extensive tools for database development and management, including advanced SQL editing, data modeling, and fully integrated version control.
Free to Use
SQL Developer is available as a free tool, which allows developers and database administrators to utilize its capabilities without the need for additional budget.
Integration with Oracle Products
Seamlessly integrates with other Oracle products and services, providing a cohesive environment for users within Oracle's ecosystem.
Cross-Platform
SQL Developer is available for multiple platforms including Windows, MacOS, and Linux, allowing flexibility in terms of development environments.
User-Friendly Interface
The tool features a highly intuitive and user-friendly graphical interface that simplifies database management tasks.
Robust Community and Support
Boasts a strong, active community and extensive official documentation, making it easier to find solutions to problems and best practices.

Possible disadvantages

Resource Intensive
SQL Developer can be quite resource-intensive, requiring a significant amount of RAM and processing power, which may affect performance on less powerful machines.
Performance Issues with Large Datasets
Performance can degrade when working with very large datasets, leading to slower query execution and application responsiveness.
Oracle-Centric
While it does support other databases like MySQL and SQL Server, its features and optimizations are primarily geared towards Oracle Database, potentially limiting its utility with other databases.
Steep Learning Curve
The extensive feature set can result in a steep learning curve for beginners who are not familiar with advanced database management and development concepts.
Occasional Stability Issues
Users have reported occasional stability issues and bugs, which can disrupt workflow and require restarts or workarounds.
Limited Collaboration Features
Lacks advanced collaboration tools, making it less effective for teams that require robust version control and collaborative features directly within the tool.

Analysis

An editorial look at what each product does well and who it suits.

Apache Spark

SQL Developer

Overall verdict

Yes, Apache Spark is generally considered good, especially for organizations and individuals that require efficient and fast data processing capabilities. It is well-supported, frequently updated, and widely adopted in the industry, making it a reliable choice for big data solutions.

Why this product is good

Apache Spark is highly valued because it provides a fast and general-purpose cluster-computing framework for big data processing. It offers extensive libraries for SQL, streaming, machine learning, and graph processing, making it versatile for various data processing needs. Its in-memory computing capability boosts the processing speed significantly compared to traditional disk-based processing. Additionally, Spark integrates well with Hadoop and other big data tools, providing a seamless ecosystem for large-scale data analysis.

Recommended for

Data scientists and engineers working with large datasets.
Organizations leveraging machine learning and analytics for decision-making.
Businesses needing real-time data processing capabilities.
Developers looking to integrate with Hadoop ecosystems.
Teams requiring robust support for multiple data sources and formats.

Overall verdict

Yes, SQL Developer is considered a good tool by many professionals in the industry. It is widely used due to its versatility and the strong support system that Oracle provides. For developers who work extensively with Oracle databases, SQL Developer can be an invaluable resource, offering tools and functionalities that enhance productivity and facilitate effective database management.

Why this product is good

SQL Developer by Oracle is designed as an integrated development environment (IDE) specifically for working with SQL, PL/SQL, Stored Procedures, and other database-related applications. It provides a user-friendly interface for database management, which covers aspects such as running queries, creating and editing database objects, and managing performance. The software is highly regarded for its robust feature set, including built-in reporting tools, data modeling capabilities, and support for version control systems, making it a comprehensive tool for database developers.

Recommended for

Database administrators who manage Oracle databases.
Developers who write and test SQL, PL/SQL, and other database scripts.
Data analysts and architects who require advanced data modeling tools.
IT professionals who need reliable, supported database management solutions.
Organizations already integrated into the Oracle ecosystem.

Videos

Walkthroughs and reviews on video.

Apache Spark 3 videos + Add

SQL Developer 1 video + Add

Weekly Apache Spark live Code Review -- look at StringIndexer multi-col (Scala) & Python testing

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100

Apache Spark

SQL Developer

57% 57%

Databases

43% 43%

0% 0%

Database Management

100% 100%

Big Data

0% 0%

100% 100%

Stream Processing

0% 0%

User comments

Share your experience with using Apache Spark and SQL Developer. For example, how are they different and which one is better?

Reviews and articles

External articles and on-site reviews we used to compare the two products.

Apache Spark no reviews yet

SQL Developer no reviews yet

15 data science tools to consider using in 2021
searchbusinessanalytics.techtarget.com · Nov 2021

Apache Spark is an open source data processing and analytics engine that can handle large amounts of data -- upward of several petabytes, according to proponents. Spark's ability to rapidly process data has fueled...
Top 15 Kafka Alternatives Popular In 2021
www.spec-india.com · Sep 2021

Apache Spark is a well-known, general-purpose, open-source analytics engine for large-scale, core data processing. It is known for its high-performance quality for data processing – batch and streaming with the help...
5 Best-Performing Tools that Build Real-Time Data Pipeline
www.analyticsinsight.net · Oct 2017

Apache Spark is an open-source and flexible in-memory framework which serves as an alternative to map-reduce for handling batch, real-time analytics and data processing workloads. It provides native bindings for the...

Best Oracle Database Tools for Developers and DBAs [Free & Paid]
blog.devart.com · Mar 2026

Oracle SQL Developer is the primary client software for Oracle Database, developed and supported directly by Oracle Corporation. As the official tool, it provides full support for all Oracle versions, both on-premises...
Top Free SQL Database Software and GUI Tools
www.devart.com · Mar 2026

Oracle SQL Developer, created by Oracle Corporation, serves as the default graphical user interface (GUI) client for Oracle Database, both on-premises and cloud-based.
7 Best Oracle GUI Tools for Windows or macOS
www.devart.com · Aug 2025

Oracle SQL Developer, provided by Oracle Corporation, stands as the official integrated development environment for Oracle Database. It comes at no extra charge with any Oracle Database license and provides a...

Social recommendations and mentions

Recommendations tracked on public social media and blogs since March 2021.

Apache Spark 80 mentions

SQL Developer 0 mentions

MLOps Lifecycle: Stages, Workflow, and Best Practices
Feature transformations should be deterministic: The same input should produce the same output when the same feature definition and configuration are applied. This is what allows training, backtesting, and live inference to remain... - Source: dev.to / 4 months ago
7 Free Tools for Data Pipeline Reconciliation and Cross-Source Validation
Apache Spark provides distributed in-memory data processing and is the appropriate tool when the data set to be reconciled does not fit in a single machine's memory, or when parallelizing the comparison across a cluster would reduce... - Source: dev.to / 5 months ago
Why Apache IoTDB Is Written in Java: A Decade of Engineering Trade-offs
When IoTDB was initiated in 2011, almost all influential distributed systems and databases were built in Java or on the JVM—such as Hadoop, HBase, Spark (Scala on JVM), Cassandra, Kafka, and Flink. To integrate deeply with the big data... - Source: dev.to / 6 months ago

Tracking SQL Developer since Mar 2021.

Alternatives to Apache Spark and SQL Developer

When comparing Apache Spark and SQL Developer, you can also consider the following products.

Apache Flink
Flink is a streaming dataflow engine that provides data distribution, communication, and fault tolerance for distributed computations.

Compare Apache Flink to Apache Spark or SQL Developer:

Apache Flink vs Apache Spark Apache Flink vs SQL Developer
phpMyAdmin
phpMyAdmin is a tool written in PHP intended to handle the administration of MySQL over the Web.

Compare phpMyAdmin to Apache Spark or SQL Developer:

phpMyAdmin vs Apache Spark phpMyAdmin vs SQL Developer
Hadoop
Open-source software for reliable, scalable, distributed computing

Compare Hadoop to Apache Spark or SQL Developer:

Hadoop vs Apache Spark Hadoop vs SQL Developer
DbVisualizer
DbVisualizer is the universal database client and SQL tool built for developers, analysts, DBAs, data engineers, and anyone working with data.

Compare DbVisualizer to Apache Spark or SQL Developer:

DbVisualizer vs Apache Spark DbVisualizer vs SQL Developer
Apache Hive
Apache Hive data warehouse software facilitates querying and managing large datasets residing in distributed storage.

Compare Apache Hive to Apache Spark or SQL Developer:

Apache Hive vs Apache Spark Apache Hive vs SQL Developer
Navicat
Powerful database management & design tool for Win, Mac & Linux. With intuitive GUI, user manages MySQL, MariaDB, SQL Server, SQLite, Oracle & PostgreSQL DB easily.

Compare Navicat to Apache Spark or SQL Developer:

Navicat vs Apache Spark Navicat vs SQL Developer