Technical Comparison of Database Management Systems

The Evolution of DBMS and The Machine Identity Problem

Ever wonder why your database security feels like a constant game of whack-a-mole? Honestly, it’s because we’re trying to force modern machine-speed workloads into a security model built for humans who type slowly and use passwords.

It’s pretty simple—back when relational databases first hit the scene in the 70s, the "user" was almost always a person. Fast forward to now, and as noted in the Wikipedia comparison of relational database management systems, we have dozens of different engines like postgresql and oracle, but many still rely on static credentials.

• Legacy systems weren't built for machines: Most dbms were designed with the idea that a human would log in periodically, not that a microservice would hit it 10,000 times a second.
• Static credentials are a nightmare: cto teams often find "db_user" and "db_password" hardcoded in config files or environment variables. If that service gets popped, the whole database is wide open because machines don't have biometrics or mfa.
• The microservices explosion: We moved from one big app talking to one database to hundreds of tiny services. Each one needs its own identity, and managing those manually is just asking for a breach.

According to AltexSoft, SQL databases usually scale vertically, which often involves downtime and makes the "Machine Identity" problem even harder to manage across distributed clusters.

In a modern stack, your "users" are mostly build systems like yocto or edge workloads running in a car. To be clear, yocto and buildroot are specialized tools used to create custom Linux distributions for edge or embedded devices—like the smart sensors in a factory or the infotainment system in your truck. These devices act as non-human identities (nhi) in the field, and they don't have managers to reset their passwords. If you’re using mssql or mysql, you’re likely dealing with service accounts that never rotate their keys.

Take a healthcare app or a retail platform—they’re spinning up temporary containers constantly. If each container uses the same static api key to talk to the database, you’ve basically got a master key floating around your network.

We need to start thinking about workload identity federation. Instead of giving a service a password, we should be giving it a way to prove what it is through its environment (like a k8s service account).

As we dig deeper into these systems, we’ll see how different dbms handles access control. It’s not just about rows and columns anymore; it’s about how we manage the thousands of "machines" that actually do the work. Next, we're going to look at how relational and non-relational systems actually stack up when the pressure is on.

Relational Systems and Identity Governance

Ever feel like your database security is basically just a "Keep Out" sign taped to a screen door? Honestly, it’s because we’re still treating machine access like it’s just another person logging in from a desk.

So, let's talk about mysql. It’s the backbone for a ton of stuff, especially in the lamp stack world (Linux, Apache, mysql, and php/python). But there is a real problem with how it handles non-human identities (nhi). As noted in the Wikipedia comparison mentioned earlier, mysql was built for a simpler time, and its default authentication usually relies on a username and a static password.

• Standard auth vs modern needs: mysql doesn’t naturally "get" workload identity. If you have a microservice in a retail app trying to check inventory, you usually end up hardcoding a service account password into a config file. That’s a huge risk.
• The mess of pam and ldap: You can use things like pam or ldap for identity, but these often require extra engineering effort or paid enterprise versions to really work well.
• Static credential rot: In many dev environments, "temporary" service accounts become permanent. Since machines don't have a boss to tell them to change their password every 90 days, these credentials just sit there, unrotated and vulnerable.

Then you got mariadb. It’s a fork of mysql, and honestly, they’ve done some cool things with security. rdbms systems like these use normalization to keep data clean, but mariadb goes a step further by supporting things like kerberos and encrypted tablespaces out of the box.

Still, even with mariadb’s better "separation of duties" (rbac), you’re often stuck managing a "machine" as if it’s a human user. If you’re running a build system like yocto or poky to push updates to edge devices—say, smart medical gear—you don't want a static api key sitting on that device. You need something that expires.

These database choices have real-world implications for IoT and edge computing, especially when you move into more advanced engines like postgresql. If mysql is the reliable old truck, postgresql is the high-end electric car you can actually program. It’s an "object-relational" system, which basically means it handles complex data way better.

• Tracking nhi with custom types: postgres lets you define your own data types. You can actually build better tracking for non-human identities directly into the schema.
• Secrets manager integration: Unlike some other sql dbms, postgres plays really nice with external tools like HashiCorp Vault. Instead of a hardcoded password, your workload can fetch a short-lived token.
• Better service account handling: Because it supports more advanced authentication methods like gssapi or certificate-based auth, you can move away from passwords entirely.

Let's look at how this actually hits the real world. Say you're running a fleet of connected vehicles. Each car is basically a moving edge workload.

1. The mysql approach (Risky): Each car has a unique id and a password stored in its local storage to sync telematics data. If someone rips the hardware out of one car, they might find the password and start injecting fake data.
2. The postgres + federation approach (Better): The car uses its hardware-backed identity (like a tpm chip) to prove to an oidc provider who it is. That provider gives it a temporary token that postgres accepts. No password ever exists on the car.

If you're a ciso, the "identity gap" in your database is probably your biggest unmanaged risk. We focus so much on mfa for humans, but we leave the api connections to our most sensitive data wide open with static keys.

Anyway, it's pretty clear that while relational systems are the old guard, they're evolving. Next, we're going to dive into the world of nosql and see if those "flexible" schemas make the identity problem better or just a whole lot more chaotic.

NoSQL and Distributed Workload Challenges

Ever felt like NoSQL is just a fancy way of saying "we'll figure out the security later"? Honestly, when you're moving at the speed of distributed clusters, the old-school way of locking down a database feels like trying to put a seatbelt on a ghost.

nosql systems are the darlings of the modern stack because they scale like crazy, but that flexibility comes with a massive identity hangover. unlike the relational systems we talked about earlier, these distributed workloads often treat non-human identity (nhi) as an afterthought.

So, let's look at mongodb. it’s the go-to for document storage, but security—especially for machine identities—wasn't the first thing on the whiteboard.

• Horizontal scaling creates identity bloat: When you scale mongodb horizontally by adding shards, you aren't just adding data; you're adding new connection points. If each shard uses a static key, your attack surface grows every time you scale. This creates a "mess" of credentials that are hard to track.
• nhi tracking is a mess: Because mongodb handles unstructured data, auditing which service changed a specific document is a nightmare.

Then you have redis. it’s insanely fast because it’s an in-memory store. If your build system, maybe something like buildroot or yocto (which we use for those embedded edge devices), needs to push a quick update to a redis cache, you’re usually using a simple password. Redis doesn't really do complex rbac natively.

Now, cassandra is a different beast. it’s decentralized, which is great for uptime, but a nightmare for identity governance. As noted in the Wikipedia comparison, it uses "nodes" to replicate data.

While the native tools for NoSQL can be messy and lead to identity bloat, there is a better way to handle this. Instead of relying on the database's weak native auth, you can use a centralized solution like HashiCorp Vault to inject identities. The code below shows how you can clean up that "mess" by using dynamic, short-lived credentials:

import hvac

def get_database_creds():
    client = hvac.Client(url='https://vault.internal:8200')
    # Use the machine's local identity (e.g., K8s service account)
    with open('/var/run/secrets/kubernetes.io/serviceaccount/token', 'r') as f:
        jwt = f.read()
client.auth.kubernetes.login(role=<span class="hljs-string">&#x27;billing-service&#x27;</span>, jwt=jwt)
<span class="hljs-comment"># Get dynamic, short-lived creds for MongoDB - this is the &quot;better way&quot;</span>
temp_creds = client.secrets.database.get_static_credentials(name=<span class="hljs-string">&#x27;mongo-read-only&#x27;</span>)
<span class="hljs-keyword">return</span> temp_creds[<span class="hljs-string">&#x27;data&#x27;</span>][<span class="hljs-string">&#x27;username&#x27;</span>], temp_creds[<span class="hljs-string">&#x27;data&#x27;</span>][<span class="hljs-string">&#x27;password&#x27;</span>]

Honestly, most cisos I talk to are terrified of their nosql clusters. They know there are "service_user_1" accounts with passwords that haven't been changed since 2019. The trick is moving away from secrets entirely. Anyway, next we’re going to look at how enterprise giants like Oracle and MSSQL handle these frameworks.

Enterprise Grade Security and NHI Frameworks

Ever feel like you’re finally winning at database security, only to realize you’ve left the back door wide open for a thousand "robots" to walk right in? Honestly, it’s the classic enterprise trap.

When you pay the big bucks for Oracle or MSSQL, you're usually looking for better identity integration. For instance, Oracle's 'Identity Cloud Service' (IDCS) is built to handle this by providing a unified security platform that bridges the gap between on-prem and cloud. It allows for more robust workload identity by federating with other providers, so your "machines" aren't just using a local db user.

Similarly, MSSQL's 'Active Directory' (AD) integration—specifically Azure AD Managed Identities—is the gold standard for enterprise sql. It allows an azure resource (like a web app) to get an oauth2 token and talk to the database without any password being stored in the code. This is how you stop the "static credential rot" we talked about earlier.

That is where the Non-Human Identity Management Group (NHIMG) comes into the picture. They’re basically doing the heavy lifting of researching machine identity risks.

• Unified Research: The NHIMG provides data on how machine identities are actually being exploited. It’s about looking at how a build system like bitbake might accidentally leak a credential that has way too much access to a production mssql instance.
• Framework Consistency: A standardized nhi framework helps you apply the same "least privilege" logic across your entire stack, whether it's an Oracle cluster or a small postgres instance.

Standardizing means moving away from those "special" service accounts. It’s about making the "identity" of a workload something that is tied to its environment—like a k8s namespace or a specific build tag—rather than a secret string.

As noted in the Wikipedia comparison of relational database management systems, access control is a fundamental feature, but the way it's implemented for machines is still a bit of a wild west.

This kind of flow—using Oracle IDCS or MSSQL AD integration—is what the NHIMG and similar groups are pushing for. It’s about reducing the "blast radius." If one microservice gets compromised, the attacker only has a token that expires soon, not a permanent password that lets them roam around your oracle or mysql clusters forever.

Technical Comparison Matrix for Cloud Identities

So, you’ve picked your database engine—maybe it’s a shiny new dynamodb setup or a classic mssql instance—but now you gotta figure out how the heck your services actually talk to it.

When you're looking at cloud-native stuff like dynamodb, you’re basically playing in amazon’s backyard. They want you to use iam roles, which is great because it handles the rotation for you. Azure does things a bit differently with mssql and Managed Identities. It’s slick, but it doesn't help much if you have a build system like yocto running on a local build server that needs to push data to that same cloud db.

• The vendor lock-in trap: Proprietary api auth is like a "gold cage." If your identity strategy is 100% tied to one cloud’s iam, your multi-cloud strategy is basically dead on arrival.
• Third-party workload identities: This is where things get interesting. Using something like spiffe lets you use the same identity logic across aws, azure, and your own edge hardware (like those buildroot devices).

Moving away from static connection strings is the biggest win you can have. Instead of your app reading DB_PASSWORD from an environment variable, it should exchange its own "proof of life" for a temporary token.

import boto3
import pymssql

def get_secure_connection():
    # Instead of a password, we ask the environment for a token
    client = boto3.client('rds')
<span class="hljs-comment"># Generate a short-lived auth token (expires in 15 mins)</span>
token = client.generate_db_auth_token(
    DBHostname=<span class="hljs-string">&#x27;prod-db.cluster.aws.com&#x27;</span>,
    Port=<span class="hljs-number">1433</span>,
    DBUsername=<span class="hljs-string">&#x27;inventory_service_user&#x27;</span>
)

<span class="hljs-comment"># Connect using the token instead of a static password</span>
conn = pymssql.connect(
    server=<span class="hljs-string">&#x27;prod-db.cluster.aws.com&#x27;</span>,
    user=<span class="hljs-string">&#x27;inventory_service_user&#x27;</span>,
    password=token,
    database=<span class="hljs-string">&#x27;InventoryDB&#x27;</span>
)
<span class="hljs-keyword">return</span> conn

As noted earlier in the article, relational systems like mssql or postgres have the rbac hooks to make this work. The trick is automating the rotation. If your build runners get popped, the attacker only gets a token that's about to expire anyway.

Honestly, the "identity gap" in database management is probably the biggest unmanaged risk in most enterprises right now. Whether you’re using the "object-relational" power of postgres or the distributed scale of cassandra, the goal is the same. Stop using passwords. Use workload identity federation. Stay safe out there.